One of the more interesting features of AdWords that advanced PPC marketers have been using is Google Dynamic Keywords. This allows you to insert the search query that the user typed in directly into your ad. How to Use AdWords Dynamic Keywords In your title or description lines, you can enter a little bit of code that will insert the users query into your ad. The text should be formatted as follows:

{KeyWord:Alternate Text}

The KeyWord: is the query that the user typed in. The Alternate Text is what the ad will display if for some reason the query cannot be shown (such as if the query string is too long, etc.).

For example, let’s say we have “Larry’s Lamps”. Larry is bidding on the keywords “brass lamps”, “brass lamp”, “quality brass lamp”, and “brass lamps sale”. The ad is set up in AdWords as follows:

If the visitor searches for “Brass Lamps”, they will see:

If the visitor searches for “Quality Brass Lamp”, they will see:

This is brilliant, because whatever the user types in will appear exactly in the ad. The ad will be properly bolded, and will appear more relevent to the visitor.

You can even control the case of the ad:

Buy {keyword:Car parts}  Buy car parts
Buy {Keyword:Car parts}  Buy Car parts
Buy {KeyWord:Car parts}  Buy Car Parts
Buy {KEYWord:Car Parts}  Buy CAR Parts
Buy {KeyWORD:Car parts}  Buy Car PARTS
Buy {KEYWORD:Car Parts}  Buy Car Parts

What is a feed?
Feeds, also known as RSS feeds, XML feeds, syndicated content, or web feeds, contain frequently updated content published by a website. They are usually used for news and blog websites, but are also used for distributing other types of digital content, including pictures, audio, or video. Feeds can also be used to deliver audio content (usually in MP3 format) which you can listen to on your computer or MP3 player. This is referred to as podcasting.

How do I view a feed?
When you visit a webpage, the Feeds button Picture of the Feeds button will change color, letting you know that feeds are available. Click the Feeds button, and then click the feed you want to see. To get content automatically, you should subscribe to a feed. For more information on Web Slices, see Web Slices: frequently asked questions.

How do I subscribe to a feed?

1.      Open Internet Explorer, FireFox, Safari or Chrome Feedburner or Google reader
2.      Go to the website that has the feed you want to subscribe to.
3.      Click the Feeds button Picture of the Feeds button to discover feeds on the webpage.
4.      Click a feed (if more than one is available). If only one feed is available, you will go directly to that page.
5.      Click Subscribe to this Feed.
6.      Type a name for the feed and select the folder to create the feed in.
7.      Click Subscribe.

How does a feed differ from a website?
A feed can have the same content as a webpage, but it’s often formatted differently. When you subscribe, the web broswer automatically checks the website and downloads new content so you can see what is new since you last visited the feed.

Does a feed subscription cost money?
No, it’s usually free to subscribe to a feed.

How can I view my subscribed feeds?
You view feeds on the Feeds tab in the Favorites Center. To view your feeds in Internet Explorer 8, click the Favorites button, and then click Feeds.

Can other programs display my subscribed feeds?

Top Picks

Web: Bloglines Simple two-pane interface, like email.

Mac OS X: NetNewsWire This elegant Mac-like aggregator is easy to use and powerful.

Windows: SharpReader Simple, but gets the job done.

Linux: Liferea A simple Gtk newsreader.

Runners-Up

AmphetaDesk A news aggregator you access through a web browser. (Mac/Win/Linux)

FeedDemon A more complicated aggregator for Windows. (Win)

FeedReader Like SharpReader, but sporadically updated. (Win)

NewsGator Read the news from within Microsoft Outlook. (Win)

NewsWatcher Based on Scopeware technology. (Win)

News Is Free Lets you create your own customized news page with feeds from the sites you’re interested in. (Web)

Novobot A smart headline viewer and news ticker that can also process almost any website. (Win)

Radio UserLand A full-stregth news-reading application, on your desktop. (Mac/Win)

rss2email Reads RSS feeds and sends each new item to you as an email. (Unix)

Straw The GNOME news aggregator.

dynamicobjects spaces Displays RSS feeds in an Outlook-like interface. (Mac/Win/Lin)

What does RSS mean?
The acronym RSS stands for Really Simple Syndication, and is used to describe the technology used in creating feeds.

What formats do feeds come in?
The most common formats are RSS and Atom. Feed formats are constantly being updated with new versions. Most Browsers supports RSS 0.91, 1.0, and 2.0, and ATOM .3, 1.0 . All web feed formats are based on XML (Extensible Markup Language), a text-based computer language used to describe and distribute structured data and documents.

Abstract

A system for ranking geospatial entities is described. In one embodiment, the system comprises an interface for receiving ranking data about a plurality of geospatial entities and an entity ranking module. The module uses a ranking mechanism to generate place ranks for the geospatial entities based on the ranking data. Ranked entity data generated by the entity ranking module is stored in a database. The entity ranking module may be configured to evaluate a plurality of diverse attributes to determine a total score for a geospatial entity. The entity ranking module may be configured to organize ranked entity data into placemark layers.

    GOOGLE / FENWICK
    SILICON VALLEY CENTER
    801 CALIFORNIA ST.
    MOUNTAIN VIEW
    CA
    94041
    US

1. A geographic information system (GIS) comprising information about a plurality of geospatial entities and configured to prioritize the geospatial entities according to a ranking mechanism.

2. The system of claim 1, wherein the ranking mechanism uses data about a meta attribute of a geospatial entity to determine the geospatial entity’s priority.

3. The system of claim 2, wherein the meta attribute comprises one of: quality of information available about the geospatial entity, an attribute of a description of the geospatial entity, and an attribute of a definition of the geospatial entity.

4. The system of claim 2, wherein the meta attribute comprises an indicator of the geospatial entity’s popularity.

5. The system of claim 2, wherein the meta attribute comprises one of: an age attribute, a stature attribute, and an importance attribute.

6. The system of claim 2, wherein the meta attribute comprises a relationship of a geospatial entity to its place in a hierarchy of geospatial entities.

7. The system of claim 1, wherein an entity of the plurality of entities comprises a collection of geospatial objects and wherein the priority of the entity is determined responsive to a characteristic of the collection of geospatial objects.

8. The system of claim 1, wherein an entity of the plurality of entities comprises a geospatial entity defined in an on-line forum and wherein the ranking mechanism uses data generated in the on-line forum to determine the rank of the geospatial entity.

9. The system of claim 1, wherein the ranking mechanism uses data harvested from a website on the internet about a geospatial entity to determine the geospatial entity’s priority.

10. The system of claim 1, wherein the ranking mechanism determines a geospatial entity’s priority from a combination of weighted data from a plurality of meta attributes of the geospatial entity.

11. A computer-implemented method for ranking geospatial entities, the method comprising: receiving geospatial entity data; evaluating attributes of geospatial entities included in the received geospatial entity data; ranking the geospatial entities based on the evaluation; and storing the ranked geospatial entity data.

12. The method of claim 11, wherein the geospatial entity data comprises data generated in a community forum.

13. The method of claim 11, wherein the geospatial entity data comprises data associated with a specific user and further comprising using the ranked geospatial entity data to generate a map for the specific user.

14. The method of claim 11, further comprising selecting geospatial entities for a geographical display based on the rankings of the geospatial entities.

15. The method of claim 11, further comprising providing the ranked geospatial entity data to a map system configured to generate a map that includes ranked geospatial entities and unranked geospatial entities.

16. The method of claim 11, further comprising selecting geospatial entities to include in navigation instructions based on rankings of the geospatial entities.

17. The method of claim 11, further comprising selecting a geospatial entity to associate with an advertising term based on the geospatial entity’s ranking.

18. The method of claim 11, further comprising providing the ranked geospatial entity data to an application for generating a search result based on the ranked geospatial entity data.

19. The method of claim 11, wherein evaluating is performed responsive to user instructions for providing personalized geospatial entity rankings.

20. The method of claim 19, wherein the user instructions comprise a weighting to be applied to an attribute of a geospatial entity identified in the geospatial entity data.

21. A system for ranking geospatial entities, the system comprising: an interface for receiving ranking data about a plurality of geospatial entities; an entity ranking module for generating place ranks for geospatial entities according to a ranking mechanism based on the ranking data; and a database for storing ranked entity data generated by the entity ranking module.

22. The system of claim 21, wherein the interface is configured to provide the ranked entity data to a requesting application.

23. The system of claim 21, wherein the entity ranking module is configured to evaluate a plurality of diverse attributes to determine a total score for a geospatial entity.

24. The system of claim 21, wherein the entity ranking module is configured to organize ranked entity data into placemark layers.

25. The system of claim 24, wherein each placemark layer corresponds to at least one of: a level of detail, a density, an altitude, and an entity category.

26. The system of claim 21, wherein the requesting application is a map server system configured to use the ranked entity data to generate a map including entities selected on the basis of place ranks.

27. The system of claim 26, wherein the entity ranking module is hosted on the map server system.

28. An entity ranking module hosted on a client device, the module for generating rankings for a plurality of geospatial entities and the module comprising: an interface for receiving entity data that defines a plurality of geospatial entities and ranking data that describes the plurality of geospatial entities; and a ranking engine for generating rankings for the geospatial entities, wherein the rankings are used to select which of the geospatial items to include in a map to be displayed on the client device.

29. The module of claim 28, further comprising a memory for storing data about a user of the client device and wherein the ranking engine is configured to apply a ranking mechanism responsive to the user data.

30. The module of claim 29, wherein the user data comprises user preferences about the relative weightings of attributes evaluated by the ranking engine.

31. The module of claim 29, wherein the user data comprises a user defined geospatial entity.

32. The module of claim 29, wherein the user data comprises an indication of a user’s interest in a geospatial entity and wherein the ranking mechanism assigns a rankings premium to the geospatial entity based on the user’s interest.

RELATED APPLICATION DATA

[0001] This application claims the benefit of U.S. Provisional Application No. 60/726,505, filed on Oct. 12, 2005, which is hereby incorporated by reference in its entirety.

BACKGROUND

[0002] 1. Field

[0003] The invention relates to mapping systems, and more particularly, to techniques for prioritizing geographical entities for placement on geographical displays.

[0004] 2. Description of the Related Art

[0005] A geographic information system (GIS) is a system for archiving, retrieving, and manipulating data that has been stored and indexed according to the geographic coordinates of its elements. The system generally can utilize a variety of data types, such as imagery, maps, and tables. Historically, GIS technology has been used for scientific and governmental investigations (e.g., to identify geographical areas adversely impacted by pollution or over-building), resource management (e.g., regional forestry observation), and development planning (e.g., suburban development of under-utilized geographic areas).

[0006] More recently, GIS technology is being integrated into Internet-based mapping applications. Users can annotate digital map locations with placemarks (e.g., designated on the map with an icon or other graphic). Some placemarks allow the user to write a brief description relevant to the location marked by the placemark, while other placemarks allow the user to change the style of icons and/or labels associated with the placemark. However, in many instances, the number of available placemarks is significant.

[0007] What is needed, therefore, are techniques for prioritizing which placemarks (as well as other map entities) to display on a GIS-based map.

SUMMARY

[0008] The above need is met by techniques for generating prioritized entity data described herein.

[0009] In an embodiment, a geographic information system (GIS) comprises information about a plurality of geospatial entities and is configured to prioritize the geospatial entities according to a ranking mechanism. The ranking mechanism uses data about a meta attribute of a geospatial entity to determine the geospatial entity’s priority. The meta attribute may vary in different implementations but in one embodiment comprises the quality of information available about a geospatial entity.

[0010] In another embodiment, a computer-implemented method can be used to rank geospatial entities. The method comprises several steps including receiving geospatial entity data, evaluating attributes of geospatial entities included in the received geospatial entity data, ranking the geospatial entities based on the evaluation, and storing the ranked geospatial entity data.

[0011] Another embodiment of the present invention provides one or more machine-readable mediums (e.g., one or more compact disks, diskettes, servers, memory sticks, or hard drives) encoded with instructions, that when executed by one or more processors, cause the one or more processors to carry out a process for ranking geospatial entities. This process can be, for example, similar to or a variation of the methodologies described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

[0012] FIG. 1 is a block diagram of a GIS system with entity ranking capabilities in accordance with an embodiment of the invention.

[0013] FIG. 2 is a block diagram of the entity ranking module shown in FIG. 1, according to one embodiment of the present invention.

[0014] FIG. 3 illustrates a method for generating and providing prioritized entities in accordance with an embodiment of the invention.

[0015] FIG. 4 illustrates a method for requesting and receiving a map including prioritized placemarks in accordance with an embodiment of the invention.

[0016] FIG. 5 depicts a GIS map that includes prioritized placemarks in accordance with an embodiment of the invention.

[0017] The figures depict various embodiments of the present invention for purposes of illustration only. One skilled in the art will readily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the invention described herein.

DETAILED DESCRIPTION

[0018] A geographic information system (GIS) is disclosed that provides users with a greater degree of flexibility, utility, and information. The system may also be configured as a distributed geographic information system (DGIS). The system employs techniques for prioritizing which placemarks (as well as other map entities) to display on a GIS-based map.

General Overview

[0019] It is common practice in Geographic Information Systems to provide mechanisms to select a subset of available geographic features for display based on any of several criteria. For example, one might load a database of world cities into such a system and then request to see only those cities within the United States, those cities with populations exceeding one million persons, or perhaps those cities meeting both of these criteria. In this last case, only the markers for New York City, Los Angeles, Chicago, Houston, Philadelphia, San Diego, Detroit, and Dallas would be displayed if 1990 population data were being used.

[0020] Further, some interactive Geographic Information Systems support different feature visibility criteria at different viewing distances. For example, a selection criteria might be constructed that would show only cities exceeding one million in population when the view was of the North American continent (viewing distance 1), then include additional cities exceeding 100,000 in population when the viewpoint is lowered to include a single state in the display area (viewing distance 2), and finally modified to include smaller cities as the view lowers within a state or county (viewing distance 3). These and related techniques are known in the GIS field as `selection` and in the computer image generation field as `visibility culling` and `level of detail management`.

[0021] An embodiment of the present invention is configured to determine `which few of many` geospatial items or entities to display on a map according to the relative importance of each entity according to its rank. Such a rank can be generated based on extrinsic factors, such as the popularity of the entity to users (e.g., quantity and/or velocity of geospatial item access), quality of information (e.g., respect for the information source of geospatial item and community stature of geospatial item’s author), and similar meta-data about the geospatial feature. For example, if many users of an interactive GIS system view a particular small city (e.g., Henderson, Nevada), then an embodiment of the present invention would be to give that city a sufficiently significant place rank for display so as to display it along with the major cities exceeding one million in population. In this way users are shown the geospatial entities most likely to be of interest in the area of their visual search within an interactive geospatial information system. The ranking of geospatial items may further be based on location, distance, or other intrinsic attributes of a geospatial feature such as position and altitude (zoom level).

[0022] Although the ranking of geospatial entities is described herein primarily in the context of choosing entities for display to a user on a map, the ranking may be used for other purposes, as will be apparent in light of this disclosure. Examples include selecting which entities should have associated keywords used for determining and displaying relevant advertising; selecting which entities should be suggested as potential origins, destinations, or waypoints in navigation computations; and other uses where an estimation of a most popular or most interesting subset of geospatial entities is desired. In such applications, ranked entity data generated in accordance with an embodiment of the present invention may be supplied to various systems in addition to or instead of a digital mapping system as required by the context.

[0023] Using such entity ranking information, a two or three-dimensional digital map can be generated that includes placemarks that correspond to geospatial entities. In one such embodiment, a map generated by a GIS may include several types of data about geospatial entities. For instance, the map may include geographic features such as the terrain, infrastructure including roads, rail routes and airports, buildings, and/or borders of a landscape. The map may also be annotated with information about government entities and services such as parks and recreational services, federal, state, or local government landmarks, and community services. These and other annotations may be presented in the form of placemarks belonging to one or more categories, including commercial placemarks that represent businesses, travel placemarks including, for instance, historical sights and tourism destinations, user-defined placemarks that have been identified and named by a user for personal or community use, and/or community placemarks that have been voluntarily defined by members of the public in a forum. In one particular embodiment, information presented on a map is organized into collections that comprise layers, such as a terrain layer, road layer, border layer, community placemark layer, etc. Other layers include `current events`, `history`, and `education`, and indicate the organizational taxonomy of the source from which they were taken. A user can interact with a map and turn on or off various layers of information. In an embodiment, a basic or core layer is provided that includes a basic subset of data (for instance, the terrain, major roads, and political borders), and the user can select additional layers to customize the map view. Various third-party content-providers and advertisers can provide individual layers of data that can be overlaid onto such a basic map.

[0024] As will be understood in light of this disclosure, the placemark ranking methods described herein can be used in combination with any conventional, proprietary, and/or emerging techniques to generate a digital map. In the case of a conventional raster map, for instance, the placemarks and other types of map data are used to create a map in a digital format such as .jpeg, .gif, or .png, at a map server and then delivered to a client. Requests to manipulate or interact with the map, are provided from the client to the server, which in turn generates the requested map view. In the case of a tiled raster map, pre-generated, rasterized images or “tiles” that include placemark data are stored at a map server. When the user submits a map query, the rasterized images are provided to the client, where they are used to create the requested map. Additional views based on, for instance, panning, zooming, or tilting the requested map can be generated at the client using the tiles. Vector-based methods can also be used to generate digital maps in accordance with other embodiments of the invention. In one such particular case, map data, including placemark data, is provided to the client by a map server in the form of vector graphic instructions. The instructions are interpreted by an application at the client in real-time to generate a map for the user. As a user interacts with the map, for instance, by including or excluding various layers including geospatial entities, the map can be dynamically updated at the client to include those layers. Likewise, as the user interacts with the map, for instance, by zooming or panning, the map can be dynamically regenerated at the client to include the new map views.

[0025] Geographic information systems (GIS) are referred to throughout the present disclosure. As is known, a GIS may be implemented as a distributed geographic information system (DGIS), in which, for instance, GIS components are distributed across two or more different computers in different physical locations across a network such as the Internet or a corporate enterprise. Reference is also made herein to Google Earth, a GIS-based digital globe that includes various elements such as servers, clients, and other components and features as will be apparent in light of this disclosure. Reference is also made to Google Earth Community, a forum in which placemarks and entities are created, defined, described, and discussed by members of the participating public. Note that “Google Earth” and “Google Earth Community” and the descriptions provided herein may be protected under other forms of intellectual property, and are used for reference purposes only.

System Architecture

[0026] FIG. 1 is a high-level diagram of a digital map system 100 with entity ranking capabilities in accordance with an embodiment of the invention. The system 100 includes a map server system 150 that is communicatively coupled to one or more clients 110 via a network 160. The map server system 150 is coupled to a database 140 of ranked entity data populated (e.g., offline, or in real-time) by a GIS 170. The GIS 170 is equipped with an entity ranking module 120A that applies a ranking mechanism or algorithm to determine the relative ranks of geospatial entities. These entities may be defined within the GIS 170, for instance, based on data provided to the GIS 170 from various external sources 180. The ranked entities are stored in a database 140 and supplied to the map server system 150, which uses the ranked entity data to generate maps for clients 110. In the system 100 shown, client-side entity ranking modules 120B-C are also present for providing additional entity ranking functionality. For instance, in accordance with an alternative embodiment, the map server system 150 may provide the ranked entity data to clients 110 for client-side generation of maps and ranked entity data layers. Principles of heavy-client and light-client functionality equally apply here, as will be apparent in light of this disclosure.

[0027] Other modules may be included in the system, and illustrated modules may be rearranged and functionalities can be distributed. For instance, the GIS 170 can be integrated into the map server system 150. Similarly, the entity ranking module 120A of the GIS may be a standalone module. There may be a single entity ranking module 120A implemented wholly in or with the GIS system 100, without any entity ranking modules 120B-C on the client side 110. In another embodiment, entity ranking is implemented strictly by entity ranking modules 120B-C at clients 110. Other configurations will be apparent in light of this disclosure, and the present invention is not intended to be limited to any particular one. In this example, the term “module” refers to computer program logic or software for providing the specified functionality. When utilized by a client device 120 or map server system 150, a module may be loaded into memory and executed on a processor. In other embodiments, a module can be implemented in hardware (e.g., gate-level logic), firmware (e.g., a microcontroller with embedded routines for carrying out entity ranking as discussed herein), software, or some combination of hardware, firmware, and/or software.

[0028] The client 110 can be any device that allows a user to access the map server system 150 via the network 160. The client 110 may a device or system configured for computing, such as a personal computer or laptop, a mobile phone, a personal digital assistant, a smartphone, a navigation system located in a vehicle, or a handheld GPS system. Other clients 110 (not shown) may also be in communication with the map server system 150 via the network 160.

[0029] Each client 110 includes an application such as a browser that allows the user to interface and communicate with systems such as the map server system 150 on the network 160, as typically done. Examples of browsers include Microsoft’s Internet Explorer browser, Netscape’s Navigator browser, Mozilla’s Firefox browser, PalmSource’s Web Browser, or any other browsing or application software capable of communicating with network 160. Alternatively or in addition, the client 110 may include an application implemented outside of a browser, such as a specialized mapping or geographic application, from which data on the map server system 150 can be accessed. Interactions with the map server system 150 may be accomplished through a plug-in or other executable architecture implemented locally.

[0030] The GIS 170 can be configured with conventional technology, but further includes an entity ranking module 120A configured in accordance with the principles of the present invention. The GIS 170 receives data from various sources 180 upon which ranked entity data can be determined by the entity ranking module 120A. Both geospatial entities and ranking data by which the geospatial entities can be ranked are represented in the data. These types of data can be provided to the GIS 170 in structured and unstructured form. For instance, while entity data in the form of city names and geographies may be provided in a structured form, ranking data in the form of community comments or ratings, for instance, may be provided in unstructured form. Or, entity data and ranking data may be provided from the same structured source that, for example, identifies a city and its population, or an unstructured source such as a community bulletin board in which an entity is defined and data by which it can be ranked is provided.

[0031] The entity ranking capability of the map system 100 is provided by one or more entity ranking modules 120. The entity ranking module 120 collects entity data and ranking data with which the geospatial entities can be rated. This data may be provided from various sources including the GIS 170, external sources 180, and the client 110. These sources are described in further detail with reference to FIG. 2. The module 120 evaluates the geospatial entities using the ranking data in order to determine a score or rank for each of the entities. In an embodiment, the module 120 also associates the entities with placemarks for a map, and generates groupings or layers of placemarks based on, for instance, a certain placemark density or map view altitude. The resulting entities and entity layers can be stored in a ranked entity database 140, at a client 110, or elsewhere. Each of these capabilities will be described in further detail with reference to FIG. 2.

[0032] In a system that includes server 120A and client-side entity ranking modules 120B-C, the client-side modules 120B-C may provide complementary rankings for use in generating a map for a client 110. In one such embodiment, a server-side entity ranking module 120A provides general placemarks whose rank is determined by a set of general ranking data, while a client-side entity ranking module 120B-C provides personal placemarks that have been ranked using personal data about a user, their behavior, or their preferences.

[0033] The network 160 may be any type of communications network, such as a local area network (e.g., intranet), wide area network (e.g., internet), or some combination thereof. Alternatively, the network 160 may be a direct connection between the client 110 and the map server system 150. In general, the client 110, network 160, and/or map server system 150 may be in communication via any type of wired or wireless connection, using a wide variety of communication protocols.

[0034] The map server system 150 can be implemented with conventional or custom technology. Numerous known server architecture and functionalities can be used to implement a GIS server system. Further, the map server system 150 may include one or more servers operating under a load balancing scheme, with each server (or a combination of servers) configured to respond to and interact with clients 110 via the network 160. In one particular embodiment, the server system 150 is implemented as discussed in U.S. application Ser. No. 10/270,272, filed Oct. 10, 2002, titled “Server for Geospatially Organized Flat File Data,” which is incorporated herein.

[0035] In general, when a user of a client computer 110 enters a search query (e.g., via browser and client side agent), it is put into a request by the client 110, and sent to the map server system 150 via the network 160. The server system 160 then determines what the search query is for, and responds with appropriate data from various sub-systems, such as geo-coders, routing engines, and local search indexes, in a format that the requesting client can use to present the data to the user (e.g., via a browser or other application).

[0036] Used in conjunction with the server system 150, the GIS 170 and ranked entity database 140 provide a map system 100 that serves map and GIS data over the Internet or other network 160. The map system 100 allows users to visualize, select, and explore geographic information (e.g., all over the world or in a particular region). The entity ranking module 120A can be configured to place rank available map data items based on various attributes associated with each geospatial feature (or a subdsdscset of geospatial features). These attributes may be extrinsic or instrinsic attributes of a geospatial feature, represent meta attributes of the feature, and/or reflect the personal behavior of a user. Based on ranking entities according to these attributes, users are shown the geospatial entities most likely to be of interest in the area of their visual search within the interactive GIS.

Entity Ranking Module

[0037] FIG. 2 is a high-level block diagram of an entity ranking module 120 that could be implemented at a client computer or server-side GIS according to one embodiment of the present invention. The entity ranking module 120 receives or collects data from various sources about geospatial entities through an interface 250. The data contains both entity data 210 that identifies and defines geospatial entities and ranking data 220 by which geospatial entities can be evaluated. The entity data 210 may comprise placemark-level data. The ranking engine 230 applies one or more ranking algorithms or rank mechanisms to the ranking data 220 to determine scores for geospatial entities defined in the entity data 210. The resulting ranked entity data may be provided through the interface 250 to a requesting application such as a mapping application. Or, the ranked entity data can be formed into placemark layers by a placemark layer generator 240. In whatever form, the ranked entity data is stored and provided to a map server system or other application. The entity ranking module 120 includes a memory 260 in which data collected, including from a client, can be stored.

[0038] The entity ranking module 120 can receive entity data 210 and ranking data 220 about entities from any number of sources. The data may include satellite data, aerial photographs, street-level photographs, digital map data, tabular data (e.g., digital yellow and white pages), and targeted database data (e.g., databases of diners, restaurants, museums, and/or schools; databases of seismic activity; database of national monuments; etc). It may also include government census and population data, building plan data, demographic data including socio-economic attributes associated with a geospatial entity such as a zip code or town, and alternative name data. In one particular embodiment, the data comprises proprietary content collected by a third-party provider and placemarks derived from it can only be accessed by users who have specifically paid for or subscribed to it.

[0039] While these sources comprise structured data about geospatial entities, definitions of geospatial entities 210 and ranking data 220 in the form of information about attributes of geospatial entities may also be provided in unstructured form. Such data can be harvested from websites on the internet, and/or culled or provided from various sources including community forums such as the Google Earth Community, online bulletin boards, or other virtual spaces in which geospatial entities may be defined and described by users in a public, private, or semi-public setting. In the case of the Google Earth Community, for example, an entity may be posted by a user, and then descriptions of the entities may be provided on subsequent postings or replies to the initial posting. The entity ranking module 120 may also receive data from one or more clients 110 that may be particular to a user or client device 110. As described in more detail below, this data can be used to customize rankings and/or a user’s experience.

[0040] Example geospatial entities include a city name and location, a user defined entity, a commercial entity, a geospatial item found in a web search, or any item (e.g., physical thing, event, or quality) having a geographic association. A geospatial entity is thus comprised of a geometry associated with a physical place (such as a set of geographic coordinates on Earth or the moon) and a description. In the case of a geospatial entity that is non-geographical in nature, such as the War of 1812, this geometry may correspond to locations associated with the event. Thus, the entity can correspond to single or multiple physical places and descriptions. For instance, geospatial entities in Google Earth can be either singleton objects or may be a hierarchical folder of objects, each object in which may be another folder or an entity. Thus, while some entities represent one geospatial object, other entities may have folders that in aggregate represent many geospatial objects. A single entity, in turn, may correspond to one or more placemarks. For instance, an entity like “Oakland gas stations” may include several different physical locations, each of which is represented by a separate placemark.

[0041] Ranking data 220 may describe attributes of entities that can be evaluated by the ranking engine 230 to determine the entity’s rank. In an embodiment, the attribute defines the interestingness of an entity to a particular user. Such interestingness can be used to rank the various geospatial entities in the area of a user’s visual search within an interactive geospatial information system (such as Google Earth), so that client-side entity display prioritizing is enabled. As will be explained in turn, “interestingness” for a geospatial entity can be determined by measuring or otherwise determining various types of extrinsic data associated with that entity. In one such embodiment, this measure, scaled by a corresponding weight, forms a bonus that augments the entity’s score or rank (e.g., by addition or multiplication). Thus, higher ranked entities can be given priority for display over lower ranked (less interesting) entities. Data intrinsic to the GIS system may also be considered, as normally done (e.g., zoom level).

[0042] In another embodiment, ranking data 220 comprises various indications of a user’s interest in certain placemarks. For instance, placemarks that have been saved or annotated by the user at the browser or application level could be deemed to be of greater interest to a user. A user’s search terms or patterns of web page access or use may also be correlated to certain geospatial entities and used by an entity ranking module 120 at the client or on a server to select placemarks for the user. In addition, placemarks that the user has defined for his or her own use may be assumed to be of high personal interest. In one such embodiment, geospatial entities including points of interest or personal relevance to the user, such as the location of the user’s house, workplace, child’s daycare, or favorite playground are identified and marked on any map in the vicinity of these elements, regardless of their relative rank as calculated by a GIS. These and other indications of user interest may be gauged from the user’s behavior, or may be in the form of preferences or instructions regarding entities affirmatively provided by the user, for instance instructing the inclusion or exclusion of specific entities or groups of entities in maps provided by a map server system. A rankings premium may be assigned to geospatial entities based on the user’s interest or preferences. User data collected at a client may be stored in the memory 260 of the entity ranking module and used by the ranking engine 230 to generate entity rankings that are personal to the user.

[0043] The ranking engine 230 comprises a module for ranking entities based on descriptions of entity attributes included in the ranking data 220. Depending on the type of data provided, the ranking engine 230 can use a variety of mechanisms to evaluate geospatial entities, which are further described below.

[0044] The entities as ranked by the ranking engine 230 are organized into layers by a placemark layer generator 240. This may be accomplished by determining a level of detail and threshold to be associated, for instance, with a given altitude or density. For instance, when a user’s query implicates a number of entities greater than a given threshold, only those entities having a place rank above a certain threshold are provided. For example, assume the given threshold for the total number of entities that can be displayed at the current map view is 50, and that the place rank threshold is 80. If a user’s query implicates over 100 geospatial entities, and 35 entities have a place rank over 80, then the server system will serve those 35 entities along with the 15 next highest ranked entities for display at the requesting client. Alternatively, all of the implicated geospatial entities generated are served to a client-side entity ranking module 120, which then determines which of those entities to display (in a similar fashion to the server-side functionality). Or, both server-side and client-side entity ranking can be carried out, where the server system serves a set of ranked entities, and a client then displays a sub-set of that served set. Placemarks can be subdivided into layers according to criteria other than altitude or density, including conceptual, spatial, temporal, or other groupings. In one particular embodiment, the placemark layer generator also applies stylings to the various placemarks and stores those with the placemark layers.

Ranking Mechanisms

[0045]

[0046] One embodiment of the present invention is a method for computing a relative ranking of a geospatial entity such as a city name and location, user defined entity, commercial entity, or geospatial item found in a web search, as compared to other such entities. These relative rankings are determined by a ranking engine 230 and are used within a GIS (e.g., as discussed with reference to client-side entity ranking of FIG. 1) to order the display of entities when not all can be selected for display, for example, to show some of the highest or lowest ranked entities, or perhaps a selected range of entities.

[0047] In an embodiment, this ranking, which can be referred to as place rank, is computed based on the weighted contributions of various non-cartographic meta attributes about a geospatial entity. Rather than directly measuring a characteristic of a physical place, such as its population, these attributes reflect traits of abstractions or representations associated with the geospatial entity. Examples include an attribute of a description of an entity (for instance, the amount of detail in the description of an entity or the number of times a description has been viewed), an attribute of a definition of an entity (e.g. the context or downloads of a definition of an entity, or attributes about the creation of an entity in a public forum), an indicator of the popularity of a geospatial entity (such as the number of views, downloads, or clicks on the entity or a placemark associated with the entity or an attribute based on a ranking or score assigned to an entity), or the relationship of an entity to its context, such as the category to which an entity belongs. Attributes that fit into each of these categories are described in greater detail below: [0048] The amount of detail in the description of an entity. Longer descriptions are given a greater score than shorter descriptions, based on the presumption that more words means more information. In one embodiment of the ranking system described herein, this bonus (increased score) is based on the number of characters in the description text irrespective of the number of bytes required to represent that character in a chosen alphabetic encoding (e.g., thereby normalizing for languages that require more data to encode). A detail penalty can be assessed when the description size is less than a selectable threshold as a means to down-weight “empty” or “signature only” texts. [0049] The number of entities created by a particular author or source. Sources that provide many entities are presumed more reliable than sources having created few entities. The rank bonus here rewards effort and experience and applies to user created entities (places or objects defined by users) as well as those taken from larger databases and from commercial vendors. [0050] The context of a publicly posted geospatial entity. Some geospatial entities originate in public forums (such as the Google Earth Community), and through this origination become associated with the context of that forum (e.g., social life in Rome). Since the context of the user’s search is also known, an embodiment of the ranking system described herein gives a rank bonus to entities posted in forums having a common or similar context with the user. [0051] The number of replies to a publicly posted geospatial entity. Some geospatial entities originate in public forums (such as the Google Earth Community) and in this context there is a potential for dialog about such an entity, where some post to a forum is the specification of the entity and subsequent posts are replies to that entity specification post with discussion or additional information. In these cases, an entity can be credited with a rank bonus based on the number of replies. The replies can be selectively counted, either automatically or manually by a moderator, in order to avoid counting non-relevant replies (e.g., off-topic, flames, or the like). [0052] The number of views of a publicly posted geospatial entity. Some geospatial entities originate in public forums (such as the Google Earth Community) and in this context there is a potential for readers of these forums to view some such posts more frequently than others. Since the frequency of viewing (or similarly actions, such as repeat viewing or bookmarking) reflects an interest in the item, an embodiment of the ranking system described herein gives a rank bonus to entities based on the number of views to the web page where the entity is described. When considered temporally, the incidence of entity views may have occurred non-uniformly over time, such as the case with a publicity spike attending an entity associated with a natural disaster. In such cases it may be preferable, for example, to consider 1000 views spread broadly over a sample interval as indicating greater interest, rather than considering 900 views in a short interval followed by 100 views over a longer interval. To reflect this variation in level of interest, an embodiment of the ranking system described herein allows the number of views to be optionally considered as a time series and apply statistical measures to analyze the distribution of interest. In one such embodiment, the entity rank bonus is greater for distributions that are even than those that are uneven, though the choice of a negative value as the weight for this bonus will effectively invert the class of distribution considered most interesting. [0053] The number of downloads of a publicly posted geospatial entity. Some geospatial entities originate in public forums (such as the Google Earth Community) and in this context there is a potential for readers of these forums to download entity data from some such posts more frequently than others. Since the frequency of downloading (e.g., user click-through to the entity) reflects a deep interest in the item, an embodiment of the ranking system described herein gives a rank bonus to entities based on the number times an entity is downloaded. When considered temporally, the incidence of entity downloads may have occurred non-uniformly over time, such as the case with a publicity spike attending an entity associated with a natural disaster. In such cases it may be preferable, for example, to consider 1000 downloads spread broadly over a sample interval as indicating greater interest, rather than considering 900 downloads in a short interval followed by 100 downloads over a longer interval. To reflect this variation in level of interest, an embodiment of the ranking system described herein allows the number of downloads to be optionally considered as a time series and apply statistical measures to analyze the distribution of interest. In one such embodiment, the entity rank bonus is greater for distributions that are even than those that are uneven, though the choice of a negative value as the weight for this bonus will effectively invert the class of distribution considered most interesting. [0054] The community stature of the author a publicly posted geospatial entity. Some geospatial entities originate in public forums (such as the Google Earth Community) and in this context there is an identified author for each entity. In these forums the authors may have a community stature or status based on number of posts, quality of posts as perceived by readers of those forums, common knowledge of an author’s stature, membership level (e.g., moderator, member, paid member, guest, etc.), and similar factors. An embodiment of the ranking system described herein gives a rank bonus to entities based on the stature of its author within such an online community. [0055] The number of entities contained within a multiple entity ensemble. For instance, geospatial entities in Google Earth can be either singleton objects or may be a hierarchical folder of objects, each object in which may be another folder or an entity. Due to this, some entities represent one geospatial object while other entities may have folders that in aggregate represent many geospatial objects. An embodiment of the ranking system described herein gives a rank bonus to aggregated collections since they contain more information. The bonus can be based, for example, on the
total number of locations in the entity (e.g., bonus=5 if 5 locations; bonus=7 if 10 locations; bonus=10 if 15 locations; and bonus=15 if 20 or more locations). A further embodiment of the ranking system described herein assigns a greater rank bonus to multiple entity ensembles when they have more internal folders rather than less internal folders. This reflects the perception that entities with a detailed segmentation using folders are likely to be more detailed in other aspects as well. In practice, this bonus is computed based on the number of folders contained within a multiple entity ensemble, either proportionally to the number of folders or in a segmented manner (e.g., bonus=5 if 5 folders; bonus=7 if 10 folders; bonus=10 if 15 folders; and bonus=15 if 20 or more folders). [0056] The relative age of an entity definition. Some geospatial entities originate in public forums (such as the Google Earth Community) and in this context there is an identified creation date for each entity. When two or more entities are similar in location they likely describe related information. To establish a further refined ranking score for such cases, an embodiment of the ranking system described herein gives a rank bonus to the older post as an encouragement for users to create entities defining new information rather than revisiting previously described locations. In another embodiment, newer data receives a higher rank because it reflects fresher and more current information. [0057] The hierarchical importance of an entity. Some geospatial entities originate in public forums (such as the Google Earth Community) and in this context there is a potential parent-child relationship for the post that defines an entity. A parent post, such as “universities in Kansas” may have several child posts (known as replies) that supply geospatial entities defining each university within the state of Kansas. The parent post, perhaps describing the location of the main administrative office of the Kansas university system, might have an individual score lower than that of its children, which identify schools attended by many thousands of individuals. To direct attention to the parent post in such cases, an embodiment of the ranking system described herein assigns a rank bonus equal to the sum of the scores of any replies to each post. The ranking is thus based on the relationship of a geospatial entity to its place in a hierarchy of geospatial entities. This assures that the initiating parent post’s score is greater than or equal to the sum of its parts. Other aggregation functions may also be used. [0058] The relative importance of an entity category or source of an entity category. Some geospatial entities originate in public forums (such as the Google Earth Community) and in this context there are divisions known as `forums`, within one of which the post that defines an entity will be located. Forums are typically topical; examples include `current events,` `history,` and `education.` The importance of these forums is not necessarily uniform. For example, `current events` entities may be less important over time than `history` entities, which are timeless. This situation is captured in an embodiment of the ranking system described herein by assigning an importance to each source of entities, or categories of entities, for instance, per forum for the Google Earth Community (or other interactive GIS), by vendor for commercial entity data, and similarly for other sources of entity data such as discovery by web search (e.g., low importance) or from official government sources (e.g., high importance). This relative source importance factor scales (e.g., multiplies) the overall score computed for an entity. [0059] The externally-ranked importance of an entity. Some geospatial entities originate in public forums (such as the Google Earth Community) and in this context there may be a score or rank associated with that entity. In the Google Earth Community Forum, for example, each ranked post may have from one to five “stars,” where five stars indicates a well-respected or otherwise highly regarded entity and one star corresponds to a poor or perhaps less respected entity. The metrics used to determine these external rankings are not necessarily uniform across multiple entity sources, so for example the entities from a Google Earth forum might have originating scores ranging from one to five stars, while geospatial entities found at a restaurant review website might be rated with zero to four “forks.” Further, not only are such metrics as “stars” and “forks” not directly compatible in origin and range, the sources of these metrics may have varying degrees of reliability. For example, on source might be a public website with anonymous contributions and ratings while the other might be a professionally-created restaurant or tourist guide reporting refereed evaluations. For these reasons, the method by which an embodiment of the ranking system described herein incorporates such data is prefixed with an initial scale (A) and offset (B) transformation (e.g., NEW=A*OLD+B) before the subsequent weighting process (e.g., AttributeScore=Weight * [NEW]). For example, if a stars-based rating scheme goes from 1 to 5 (i.e, 0% to 100% satisfaction) and a forks-based scheme goes from 0 to 4 (i.e., 0% to 100% satisfaction), then the ratings cannot be compared or processed just by multiplying, since they start at a different values (1 vs. 0). One technique for handling this case of diverse rating systems is to take the entity source’s native range (Low . . . High) and compute the following: Rescaled=(NativeValue-Low)/(High-Low). This maps any range into 0 as low and 1 as high. Then, the result (Rescaled) can be multiplied by a weighting factor (e.g., 100) to allow the entity to gain from 0 to 100 points of rank bonus as the native ranking moves from 1 . . . 5 stars or 0 . . . 4 forks. The values of Low and High are constant for each entity source (Forks, Stars, etc). Using algebra, the resealing equation can be reordered as: Rescaled=[1/(High-Low)] * NativeValue+[Low/(Low-High)] or, A=1/(High-Low) and B=Low/(Low-High). It follows then that Rescaled=A*Native+B. The entity score can then be augmented by WeightForThisAttribute*Rescaled (for each entity obtained from that source). One extension of such an embodiment uses the place ranking computed for an entity by the place rank process described herein to update the external-rank provided at the source where the entity was originally located, which could be for example the Google Earth Community Forums or other GIS forums. [0060] The spatial density of entities in a defined neighborhood. When multiple entities are clustered in a relatively small geographical region, this signifies that authors of the entities have indicated a geographical region of elevated interest. From this it can be assumed that an entity with an elevated density of neighboring entities has a greater value than would otherwise be the case. This is implemented in an embodiment of the ranking system described herein by adding or otherwise providing a rank bonus based on the number of other entities within a defined area that includes an entity’s location (e.g., circle or box centered at an entity’s location). Note that this metric, though geospatial in concept, is not an inherent attribute of an entity but rather an observation of that entity in relation to other entities.

[0061] The click-through rate of displayed entities. When entities are displayed in an interactive GIS such as Google Earth, it is possible to track the number of instances where users further investigate an entity by various means such as clicking on it with a mouse operation, by performing operations on that entity such as selection or highlighting; by using that entity as a routing origin, destination, or waypoint; or by finding that entity to be responsive to a search for information (e.g., as when the entity description contains the word “Pizza” and a user of the interactive system performs a search with the keyword “Pizza”, “Italian”, or “Food”). A tabulation of such events yields a direct measure of importance for that entity as understood by users of the system. When this data is collected (e.g., in the optional client entity ranking module and/or in the server-side entity ranking module) it may be used as an attribute defining interestingness for an entity. An embodiment of the ranking system described herein exploits this measured activity level by assigning a rank bonus to an entity based on the number of user events it receives compared to the average value for other entities. This measure (e.g., scaled by the corresponding weight) forms a bonus added (e.g., or otherwise used) to augment an entity’s score. [0062] The enablement rate of entity categories. When entities are displayed in an interactive GIS such as Google Earth, they are often presented in the form of layers, as described earlier. These layers are selectable individually and in aggregate. The enablement of each layer can be viewed as a vote in a plurality voting system and the aggregation of such votes may be used to determine the relative preferences that users have for the various entity data layers. When this data is collected (e.g., in the optional client entity ranking module and/or in the server-side entity ranking module) it may be used as an attribute defining relative interestingness for a collection of entities. For example, a layer of “Bars and Night Clubs” will likely be enabled more often than a layer of state “IRS Offices”. An embodiment of the ranking system described herein exploits this measured activity level by assigning a relative weighting for a class of entities or source of entities based on the number of layer selection actions observed compared to an average value. This measure can be used to set the relative importance of an entity category as previously discussed, or may be used to scale those static priorities by an additional amount based on empirical observation of user preferences. [0063] The estimated importance of the web page or document associated with an entity. When an entity is linked from a web page or other electronic document, it is possible to use the estimated importance of that page or document to infer the estimated importance of the linked geospatial entity. One estimate of relative importance for online documents is a page rank, such as described in U.S. Pat. No. 6,285,999, titled “Method for Node Ranking in a Linked Database” and/or U.S. Pat. No. 6,799,176, titled “Method for Scoring Documents in a Linked Database” and/or U.S. Patent Application No. 20050071741, titled “Information Retrieval Based on Historical Data,” each of which are hereby incorporated by reference herein. An embodiment of the ranking system described herein uses such page rank scores as a proxy score for geospatial entities referenced by online documents identified in a search result. For example, a Google search for “Kansas university” returns 1,560,000 results, which are ordered by the page rank mechanism described in the ’999 patent to display the ten results deemed most relevant as the initial response to the query. These first ten results are exactly those having the highest page rank score. An embodiment of the present invention uses one or more of search result document page rank scores, scaled by the corresponding weighting factor, as an importance bonus for geospatial entities referenced by those documents. For example, the top page rank score may be used, or the average of the top ten page rank scores, or some other function or selection thereof.

[0064] One or more of the attributes listed above is evaluated and the results are weighted individually with a scale factor before being summed to produce an overall score for an entity. Such a calculation could be performed by the ranking engine depicted in FIG. 2. In an embodiment, both meta attribute data about a geospatial entity and data that reflects attributes of the entity itself are used to determine the overall score. For instance, in an embodiment, the size of a business and the number of replies to a posting about the business are both factors that are weighed by a ranking engine 230. The ordering of entities by non-increasing score defines the ranking (descending order). The weighting factors can be changed based on resulting rankings to adjust the relative prominence of each attribute (e.g., automatically, or as desired by the system administrator, or by an individual user). In one embodiment, an end user can assign the weights to be applied to each type of attribute. Any of the weightings can be set to zero (or one in the case of relative importance) to remove that attribute from consideration or equivalently some of the attributes may be ignored. The weighting factors can be made negative to downgrade rather than reward entities for a particular attribute. Applying scale factors to individual attributes allows diverse attributes to be evaluated and a total score to be calculated based on the attributes.

[0065] Numerous algorithms can be used to for determine place rank in accordance with an embodiment of the present invention. For example, in an embodiment, SCORE=NumberOfPostCharacters+a * NumberOfDescriptionCharacters)+b* NumberOfReplies+c* NumberOfViews+d * NumberOfDownloads+StatureWithinCommunity, wherein a, b, c, and d represent variables that can be adjusted based on the value assigned to each attribute. The StatureWithinCommunity reflects the poster of a description, and, in an embodiment, can range from 200 to 500 depending on the poster’s stature based on any of a number of criteria including reputation, posting behavior, and ratings or endorsements by other users.

[0066] One embodiment of the ranking system described herein aggregates the individual attribute measures with a general linear combination. A more sophisticated aggregation, of which the linear combination is the subset along the main diagonal, is to use an M by M matrix of weights, where the dimension M corresponds to the number of attributes, and matrix reduction is used to allow specification of weights for the full cross product of attributes. For example, such a technique allows a specified weight for the product of `description length` and `author stature` as a combined component. The two equation structures described herein are representative of the variety of attribute combination methods that will be apparent in light of this disclosure, such as including exponentiation or other algebraic forms in the evaluation of each attribute.

[0067] Thus, extrinsic meta data about a geospatial entity can be used as input to a scoring system that produces a relative ranking for purposes such as selection for display within a geospatial information system. There are other attributes that may be used in such a system, such as the degree of match between search terms and entity description text and historical search preferences of an individual user or users in aggregate, that may be incorporated into an interactive GIS as described herein as elements used to determine an entity score. Further, as described earlier, the ranking may be used for purposes other than selection for display.

[0068] FIGS. 3 and 4 are flow charts illustrating steps performed to generate and serve ranked entity data in accordance with embodiments of the invention. Not every possible step is shown in the figures. In addition, some embodiments perform different steps in addition to, or instead of, the ones described herein. Furthermore, the order of the steps can vary from that described herein.

Generating Prioritized Placemarks for a Map

[0069] FIG. 3 illustrates a method for generating and providing prioritized entities in accordance with an embodiment of the invention. One or more steps may be performed by an entity ranking module such as the one depicted in FIG. 2 and implemented on the client and/or server side as shown in FIG. 1. In addition, while certain steps (for instance 350) are triggered by a user request for a map, others may be performed `off-line` outside the context of a particular search request.

[0070] On a regular basis, entity data is received 310 from various sources such as the data sources discussed with reference to FIG. 1. Ranking data is also received 320, from the same or different sources as the entity data. The collection of data may take place, for instance, as part of a database construction process, or a web crawl and indexing process. Such data may also be pushed from vendors or third party sources. Some portions of the data, for instance, data about a user’s personal placemarks, may be updated in real-time in response to a user request while others are received or refreshed according to a regular schedule. Various mechanisms such as those described above may be applied to the ranking data to determine 330 rankings or scores for the entities. Comparable attribute scores based on disparate types of ranking data obtained from various sources can be calculated using the techniques described above. The entity data may be stored in a database such as the one shown in FIG. 1, or in another embodiment, a subset of the ranked entity data is cached in a memory of a client hosting an entity ranking module that determines 330 entity rankings based on the cached data.

[0071] According to the example method shown in FIG. 3, ranked entity data is used to generate 340 layers of placemarks for display on maps. In an embodiment, the entities are mapped to placemarks, and stylings are applied based on the category in which an entity or placemark falls. Groups of placemarks are correlated to levels of detail in order to present a viewer of a map with an appropriate density of placemarks. The levels of detail may reflect any number of inputs, including the altitude at which a map is being viewed, the resolution of the map, other layers depicted on a given map, and user preferences about how sparse or dense a map should be. For instance, in an embodiment, if a placemark score is beyond a certain threshold, it receives a level 5 rating, meaning that map views at or below a certain altitude should include the placemark. The placemarks may also be organized into categories such that an individual placemark can be associated with different groups of placemarks, e.g. placemarks associated with a specific city as well as placemarks of tourist destinations. Each of these categories may be reflected a separate placemark layer.

[0072] In an embodiment, at a later point in time, a request for a placemark layer or layers is received 345, and the appropriate layers are provided 350 to the requester. As discussed earlier, a digital map may be generated according to raster, tiled, or vector-based methods. Depending on the method used, a placemark layer may be requested by a map server in real-time in response to a query, or provided 350 to create map components that are pre-stored and only served when a user request is received. In an embodiment, the placemark layers are provided 350 in response to user preferences or selections. In an embodiment, once provided, the placemark layer is combined with other layers to form a map, at a client or server site.

Requesting a Map with Prioritized Placemarks

[0073] FIG. 4 is a flow chart illustrating steps for requesting and receiving a map including prioritized placemarks in accordance with an embodiment of the invention. FIG. 5. illustrates a map that could be received based on a request formulated using steps in the processes depicted in FIG. 4. One or more of these steps may be performed at a client requesting a map from a map server as shown in FIG. 1. The process begins when a map is requested 410 by a client, for instance from within a browser, specialized application such as Google Earth, or other software application. The map request identifies the geographic area for which the map is sought and the altitude the map should represent. User or client data and preferences are also provided 420 to a map server system. For instance, in an embodiment, the country from which the request originates, which can be determined based on the IP address of the request, for instance, and a user’s language preferences are provided to a map server so that only placemarks in the appropriate language and which reflect country or culture-specific stylings or sources of data are served. The country and language information may be provided 420 from the requesting application or another source such as the operating system of the client.

[0074] In addition, user placemark preferences may also be provided 420 to the map system. The preferences may reflect for instance, which categories or layers of placemarks to display, how many placemark to include (density), and how much identifying information should be displayed on a map. For instance, in the case of the map of FIG. 5, a user can select, using checkboxes on a graphical user interface 520, which layers should be included on the map displayed 550. Each layer of placemarks is associated with its own icon or styling, for instance, a knife and fork icon 51 OA for a dining placemark, and a cup 510B for a drinking establishment.

[0075] In an embodiment, preferences provided 420 to the map system can be used to personalize the selection and display of placemarks to the user. Personalized placemark selection may be accomplished in a variety of ways, for instance by personalizing entity ranking by using a user’s behavior or usage patterns as the basis of an attribute upon which an entity’s rank is scored or varying the weight given to certain attributes based on a user’s input; or, for example, by overriding generalized ranking schemes by always including placemarks that the user has defined or designated herself.

[0076] In the flow chart of FIG. 4, a requester may receive 432 various types of data depending on the personalization preferences provided to the map server system. However, as one of skill in the art would know, other steps reflecting different map generation and customization processes are also possible. In a default embodiment, there are no personalized placemarks 430A, and the client receives 432A and displays 450A a map with general placemarks. In such an embodiment, no entity ranking capabilities are implemented locally at the client. In another embodiment, however, a client requests that the requested map include only personalized placemarks 430C. In such an embodiment, entity ranking capabilities are implemented wholly at the client, with an entity ranking module such as the module described in FIG. 2 hosted locally rather than on a centralized server. The client receives 432A a map, comprised of map layers, which does not include any placemarks on it. Personalized placemarks generated and stored at the client are added 440A to the map, and the resulting map is generated and displayed for the user.

[0077] In yet another embodiment, the user may request a map that includes both personal and general placemarks 430. The client receives 432B a map and a group of general placemarks or entities associated with the geography of the map based on this request. The general placemarks are combined with personal placemarks that have been designated by the user in any of a variety of ways (for instance by authoring the entity definition or placing the placemark in a favorites folder), and a ranking mechanism is applied 436B to the combined group of placemarks. The results are used to generate 440B a layer that includes both personal and generalized placemarks, which is then combined with the map provided to the client to generate 450B a map for display 450B.

[0078] FIG. 5 shows an exemplary map including personal and general placemarks that has been generated in accordance with the method described at steps 412-420 and 430B through 450B. As is shown in FIG. 5, personal placemarks including Max’s playground 105 and Dirk’s coffee spot 419 are depicted together with dining (e.g. 510A) and drinking placemarks (e.g. 510B) on the map 550. Also provided are community placemarks which are demarcated with a special community placemark icon 540. The map 550 also includes interactive content, in the form of a text box 530 that links to a comment about a placemark provided by a community member. This allows a user to benefit from the input provided by other community members.

[0079] The features and advantages described herein are not all-inclusive and, in particular, many additional features and advantages will be apparent to one of ordinary skill in the art in view of the figures and description. Moreover, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and not to limit the scope of the inventive subject matter.

Ranking Domains Using Domain Maturity
Invented by Janine Crumb, Krishna C Gade, Rangan Majumder, Vishnu Challam
Assigned to Microsoft
US Patent Application 20080086467
Published April 10, 2008
Filed October 10, 2006

Abstract

Ranking domains for search engines is provided herein. To rank a domain, contributing domains associated with the domain are identified. Additionally, the maturity of each of the contributing domains is determined. A rank for the domain is then determined based at least in part on the maturity of each of the contributing domains. The domain rankings may then be used to order results for search queries.

    SHOOK, HARDY & BACON L.L.P.;(c/o MICROSOFT CORPORATION)
    INTELLECTUAL PROPERTY DEPARTMENT, 2555 GRAND BOULEVARD
    KANSAS CITY
    MO
    64108-2613
    US

1. A method for ranking a domain, the method comprising:receiving a list of one or more contributing domains associated with the domain;determining a maturity for at least one of the one or more contributing domains; andcalculating a rank for the domain based at least in part on the maturity for the at least one of the one or more contributing domains.

2. The method of claim 1, wherein determining the maturity for at least one of the one or more contributing domains comprises identifying at least one of the one or more contributing domains as a mature domain.

3. The method of claim 2, wherein the mature domain is identified based on factors comprising at least one of a date of domain registration and a date of first discovery of the mature domain.

4. The method of claim 3, wherein the mature domain is a contributing domain that has been registered for more than one year without having expired or being swapped.

5. The method of claim 2, wherein calculating the rank for the domain comprises calculating the rank based at least in part on a rank of the mature domain.

6. The method of claim 1, wherein determining the maturity for at least one of the one or more contributing domains comprises identifying at least one of the one or more contributing domains as an immature domain; andwherein calculating the rank for the domain comprises calculating the rank based at least in part on a rank of the immature domain, wherein the rank of the immature domain is based on contributing domains associated with the immature domain that have been identified as mature domains.

7. The method of claim 1, wherein calculating the rank for the domain comprises calculating the rank based on a fraction of a number associated with at least one of the one or more contributing domains, wherein the fraction of the number associated with the at least one of the one or more contributing domains corresponds to the maturity of the at least one of the one or more contributing domains.

8. The method of claim 1, wherein each of the one or more contributing domains comprise a domain that includes at least one link to the domain.

9. The method of claim 1, further comprising using the rank of the domain to facilitate ordering results for a search query that include the domain.

10. A method for presenting search results, the method comprising:receiving information associated with a plurality of domains;determining a maturity for each of one or more contributing domains associated with each of the plurality of domains;calculating a rank for each of the plurality of domains based at least in part on the maturity for at least one of the one or more contributing domains associated with the each of the plurality of domains;in response to receiving a search query, generating one or more search results comprising at least one of the plurality of domains that match the search query; andpresenting the one or more search results in accordance with ranks of the at least one of the plurality of domains that match the search query.

11. The method of claim 10, wherein determining the maturity for each of the one or more contributing domains associated with each of the plurality of domains comprises identifying at least one of the one or more contributing domains as a mature domain.

12. The method of claim 11, wherein calculating the rank for each of the plurality of domains comprises calculating the rank based at least in part on a rank of the mature domain.

13. The method of claim 11, wherein determining the maturity for each of the one or more contributing domains associated with each of the plurality of domains comprises identifying at least one of the one or more contributing domains as an immature domain; andwherein calculating the rank for each of the plurality of domains comprises calculating the rank based at least in part on a rank of the mature domain and a rank of the immature domain, wherein the rank of the immature domain is based only on contributing domains associated with the immature domain that have been identified as mature domains.

14. The method of claim 10, wherein calculating the rank for each of the plurality of domains comprises calculating the rank based on a fraction of a rank associated with at least one of the one or more contributing domains, wherein the fraction of the rank associated with the at least one of the one or more contributing domains corresponds to the maturity of the at least one of the one or more contributing domains.

15. A search engine for ranking search results, the search engine comprising:a ranking component configured to determine one or more contributing domains associated with each of a plurality of domains, to determine a maturity for each of the one or more contributing domains, and to calculate a rank for each of the plurality of domains based at least in part on the maturity for at least one of the one or more contributing domains; anda searching component configured to perform a search in response to a search query and to return one or more search results comprising at least one of the plurality of domains that match the search query.

16. The search engine of claim 15, further comprising a user interface component configured to receive the search query and to present the one or more search results in accordance with the ranks of the at least one of the plurality of domains that match the search query.

17. The search engine of claim 15, wherein the ranking component is further configured to determine the maturity for each of the one or more contributing domains by identifying at least one of the one or more contributing domains as a mature domain.

18. The search engine of claim 17, wherein the ranking component is further configured to calculate the rank for each of the plurality of domains based at least in part on a rank of the mature domain.

19. The search engine of claim 17, wherein the ranking component is further configured to determine the maturity for each of the one or more contributing domains by identifying at least one of the one or more contributing domains as an immature domain and to calculate the rank for each of the plurality of domains based at least in part on a rank of the mature domain and a rank of the immature domain, wherein the rank of the immature domain is based only on contributing domains associated with the immature domain that have been identified as mature domains.

20. The search engine of claim 15, wherein the ranking component is further configured to calculate the rank for each of the plurality of domains based on a fraction of a rank associated with at least one of the one or more contributing domains, wherein the fraction of the rank associated with the at least one of the one or more contributing domains corresponds to the maturity of the at least one of the one or more contributing domains.

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001]Not Applicable.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002]Not Applicable.

BACKGROUND

[0003]Domain ranking is frequently used by search engines to facilitate the ordering of results for a search query. In general, a domain may be ranked based in part on the number of contributing domains associated with that domain. A contributing domain may be, for instance, one that includes a link to the domain being ranked. For example, if hundreds of other domains that maintain at least one web site include one or more links to a particular domain, the domain may receive a higher rank than another domain that is referenced by just a few other domains. In addition to the number of contributing domains, ranks of the contributing domains may influence the rank for the domain as well. For example, if a trusted, popular domain, such as Yahoo.com or CNN.com, includes a link to the domain, the ranks for such popular domains may be attributed to the rank for the domain. Receiving a higher domain ranking often means that the domain would be listed above other competing domains, thereby affording more visits by those browsing or searching the Internet. For domains that maintain commercial web sites or web sites that charge advertisers on per-click or per-visit basis, a higher domain ranking means better profitability. For example, sites like Yahoo.com and CNN.com, which are visited by millions of people each day, attract many commercial advertisers who are willing to pay large fees.

[0004]Typically, a domain includes links to other domains to make its content more useful and attractive for its visitors. Most existing domain ranking algorithms often assume that a number of contributing domains that maintain one or more links to a particular domain provides an indication of the popularity or utility of the particular domain. Those algorithms also tend to assume that the particular domain is popular and/or useful if a link is included in another domain that is well-known for its popularity and utility, such as MSN.com. These assumptions have been held to be mostly correct when it was neither easy nor cheap to register and maintain a domain.

[0005]Due in part to increased competition in the domain registration market in recent years, however, the cost involved in purchasing a domain has decreased significantly. In some cases, domain registrars even offer free domain registrations for up to thirty to sixty day trial periods. Spammers often take advantage of such offers through a spam technique known as a web farm. In particular, spammers purchase or otherwise obtain a large number of sites and interlink the sites together to increase the sites’ rankings by artificially increasing the number of contributing domains for some or all of the sites. In effect, this practice defeats the assumption that the more a domain is referenced by other domains, the more likely that the domains is popular and/or useful such that it should be highly ranked.

SUMMARY

[0006]This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

[0007]Embodiments of the present invention relate to, among other things, ranking a domain. One or more contributing domains associated with a target domain are identified and the maturity of the contributing domains is determined. By way of example only and not limitation, the maturity of a contributing domain may be determined based on the date that it was registered or the date that it was first discovered by a search engine. A rank for the target domain is then calculated based on the maturity of the contributing domains associated with that target domain. Accordingly, when a search engine receives a search query, results may be ordered based at least in part on the domain rankings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

[0008]The present invention is described in detail below with reference to the attached drawing figures, wherein:

[0009]FIG. 1 is a block diagram of an exemplary computing environment suitable for use in implementing the present invention;

[0010]FIG. 2 is a block diagram of an exemplary system in which embodiments of the present invention may be employed;

[0011]FIG. 3 is a block diagram of an exemplary search engine in accordance with an embodiment of the present invention;

[0012]FIG. 4 is a flow diagram showing a method for ranking a domain in accordance with an embodiment of the present invention; and

[0013]FIG. 5. is a flow diagram showing a method for presenting search results in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION

[0014]The subject matter of the present invention is described with specificity herein to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different steps or combinations of steps similar to the ones described in this document, in conjunction with other present or future technologies. Moreover, although the terms “step” and/or “block” may be used herein to connote different elements of methods employed, the terms should not be interpreted as implying any particular order among or between various steps herein disclosed unless and except when the order of individual steps is explicitly described.

Overview

[0015]Embodiments of the present invention provide an approach for ranking a domain based on the maturity of contributing domains associated with the domain. By way of example only and not limitation, a maturity of a contributing domain may be based on the date that the contributing domain was registered or the date that the contributing domain was first discovered by a search engine.

[0016]Less mature (i.e., newer) domains typically have a higher likelihood of being spam and/or being a part of a web farm that attempts to artificially inflate domain rankings for domains in the web farm. Accordingly, by taking into account the maturity of contributing domains when determining a rank for a domain, embodiments of the present invention provide domain rankings in which more relevant and useful domains may be ranked higher than spam domains and/or less relevant domains.

[0017]Accordingly, in one aspect, an embodiment of the present invention is directed to a method for ranking a domain. The method includes receiving a list of one or more contributing domains associated with the domain. The method also includes determining a maturity for at least one of the contributing domains. The method further includes calculating a rank for the domain based at least in part on the maturity for the contributing domain.

[0018]In another aspect of the invention, an embodiment is directed to a method for presenting search results. The method includes receiving information associated with a number of domains. The method also includes determining a maturity for each of one or more contributing domains associated with each domain. The method further includes calculating a rank for each of the domains based at least in part on the maturity for the contributing domains associated with the each domain. The method also includes generating one or more search results that include domains that match a search query. The method still further includes presenting the search results in accordance with ranks of the domains that match the search query.

[0019]In a further aspect, an embodiment of the present invention is directed to a search engine for ranking search results. The search engine includes a ranking component configured to determine one or more contributing domains associated with each of a number of domains. The ranking component is also configured to determine a maturity for each of the contributing domains and to calculate a rank for each of the domains based at least in part on the maturity for at least one of the contributing domains. The search engine also includes a searching component configured to perform a search in response to a search query and to return one or more search results comprising at least one of the domains that match the search query.

Exemplary Operating Environment

[0020]Referring to the drawings in general and initially to FIG. 1 in particular, an exemplary operating environment for implementing embodiments of the present invention is shown and designated generally as computing device 100. Computing device 100 is but one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention. Neither should the computing device 100 be interpreted as having any dependency or requirement relating to any one or combination of components illustrated.

[0021]The invention may be described in the general context of computer code or machine-useable instructions, including computer-executable instructions such as program modules, being executed by a computer or other machine, such as a personal data assistant or other handheld device. Generally, program modules including routines, programs, objects, components, data structures, etc., refer to code that perform particular tasks or implement particular abstract data types. The invention may be practiced in a variety of system configurations, including hand-held devices, consumer electronics, general-purpose computers, more specialty computing devices, etc. The invention may also be practiced in distributed computing environments where tasks are performed by remote-processing devices that are linked through a communications network.

[0022]Computing device 100 includes a bus 110 that directly or indirectly couples the following devices: memory 112, one or more processors 114, one or more presentation components 116, input/output (I/O) ports 118, I/O components 120, and an illustrative power supply 122. Bus 110 represents what may be one or more busses (such as an address bus, data bus, or combination thereof). Although the various blocks of FIG. 1 are shown with lines for the sake of clarity, in reality, delineating various components is not so clear, and metaphorically, the lines would more accurately be grey and fuzzy. For example, one may consider a presentation component such as a display device to be an I/O component. Also, processors have memory. We recognize that such is the nature of the art, and reiterate that the diagram of FIG. 1 is merely illustrative of an exemplary computing device that can be used in connection with one or more embodiments of the present invention. Distinction is not made between such categories as “workstation,” “server,” “laptop,” “hand-held device,” etc., as all are contemplated within the scope of FIG. 1 and reference to “computing device.”

[0023]Computing device 100 typically includes a variety of computer-readable media. By way of example, and not limitation, computer-readable media may comprises Random Access Memory (RAM); Read Only Memory (ROM); Electronically Erasable Programmable Read Only Memory (EEPROM); flash memory or other memory technologies; CDROM, digital versatile disks (DVD) or other optical or holographic media; magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, carrier wave, or any other medium that can be used to encode desired information and be accessed by computing device 100.

[0024]Memory 112 includes computer-storage media in the form of volatile and/or nonvolatile memory. The memory may be removable, nonremovable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical-disc drives, etc. Computing device 100 includes one or more processors that read data from various entities such as memory 112 or I/O components 120. Presentation component(s) 116 present data indications to a user or other device. Exemplary presentation components include a display device, speaker, printing component, vibrating component, etc.

[0025]I/O port(s) 118 allow computing device 100 to be logically coupled to other devices including I/O components 120, some of which may be built in. Illustrative components include a microphone, joystick, game pad, satellite dish, scanner, printer, wireless device, etc.

Exemplary System

[0026]Referring now to FIG. 2, a block diagram is provided illustrating an exemplary system 200 in which embodiments of the present invention may be employed. It should be understood that this and other arrangements described herein are set forth only as examples. Other arrangements and elements (e.g., machines, interfaces, functions, orders, and groupings of functions, etc.) can be used in addition to or instead of those shown, and some elements may be omitted altogether. Further, many of the elements described herein are functional entities that may be implemented as discrete or distributed components or in conjunction with other components, and in any suitable combination and location. Various functions described herein as being performed by one or more entities may be carried out by hardware, firmware, and/or software. For instance, various functions may be carried out by a processor executing instructions stored in memory.

[0027]Among other components not shown, the system 200 may include multiple client devices, such as client device 202, multiple source devices, such as source device 204, and a search engine 208. Each of the client devices, source devices, and search engine may be any type of computing device, such as computing device 100 described with reference to FIG. 1, for example. The components may communicate with each other via a network 206, which may include, without limitation, one or more local area networks (LANs) and/or wide area networks (WANs). Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet. It should be understood that any number of client devices, source devices, search engines, and networks may be employed within system 200 within the scope of the present invention.

[0028]Source devices, such as the source device 204, may maintain a variety of domains. For example, the source device 204 may be a web server that maintains multiple domains. The search engine 208 may access domain information by communicating with these source devices. For example, the search engine 208 may periodically crawl the source device 204 to access and/or update domain information, such as domain registration date, domain expiration date, domain swapping date(s), and a set of linked domains.

[0029]The search engine 208 accesses domain information from the multitude of source devices, such as the source device 204, and determines a rank for each of the domains maintained by the source devices. The ranks may be used to sort the domains when users access the search engine 208 to search for particular domains through the client device 202.

[0030]Referring now to FIG. 3, an exemplary search engine 300 in accordance with an embodiment of the present invention will be described in further detail. Among other components not shown, the search engine may include a searching component 302, a ranking component 304, a database 308, and a user interface component 306. Each component may comprise a program, routine, application, or other machine-executable code capable of performing the actions discussed herein. One skilled in the art will recognize that the components shown in FIG. 3 are provided for illustrative purposes only and other arrangements may be provided in accordance with various embodiments of the present invention.

[0031]Generally, the search engine 300 may receive search queries from client devices, such as the client device 202 of FIG. 2, via the user interface component 306. The user interface component 306 may communicate to receive search queries from client devices and pass the search queries to the searching component 302 for performing searches. The user interface component 306 may also communicate to receive search results from the searching component 302 and return the search results to the client devices.

[0032]The searching component 302 may receive a search query from the user interface component 306 and perform a search to generate search results comprising domains stored in the database 308 that match the search query in accordance with the ranks of the domains. The searching component 302 may also return the search results to the user interface component 306, which may generate a search results user interface and provide the search results user interface to the requesting client device.

[0033]The ranking component 304 may collect information associated with various domains from one or more source devices, such as the source device 204 of FIG. 2, by, for example, crawling the source devices. The ranking component 304 may determine contributing domains associated with each domain, determine a maturity for each of the contributing domains, and calculate a rank for each domain based on the maturity of the contributing domains associated with a respective domain. In some embodiments, the ranking component 304 may also save domain information and domain ranks in the database 308. In some embodiments, the maturity of a contributing domain is determined based on the date that the contributing domain was registered or the date that the contributing domain was first discovered by a search engine (e.g., when domain information does not readily provide a registration date). In some embodiments, determining the maturity of a domain also includes identifying the domain as either a mature domain or an immature domain. For example, all contributing domains that were registered more than a year ago may be identified as mature domains.

[0034]In some embodiments, a domain’s rank is calculated based in part on only mature contributing domains that are associated with the domain. For example, suppose a target domain called ClickHereForSearch.com is linked to by four other domains, Yahoo.com, MSN.com, CNN.com, and SearchesRus.com. Suppose further that the first three domains have been registered for more than one year while SearchesRus.com is a new domain that was registered less than two months ago. If, in the present example, a mature domain is defined as a domain that has been registered for more than a year without being expired or swapped, the domains, Yahoo.com, MSN.com, and CNN.com, would be identified as mature domains while SearchesRus.com would not. A rank for ClickHereForSearch.com may then be calculated based on linking from Yahoo.com, MSN.com, and CNN.com only (i.e., the mature domains) because SearchesRus.com is not a mature domain.

[0035]In other embodiments, a domain’s rank may be calculated based, at least in part, on the presence of both mature and immature contributing domains. In such embodiments, the contribution of immature domains to a target domain’s rank would be based only on the rank that the immature contributing domains received from mature domains associated with the immature contributing domains. Such embodiments recognize that although new domains often tend to be spam, not all new domains are spam and that, in fact, there are typically new domains that provide great utility. These embodiments assure that immature domains that quickly gather popularity for their utility are allowed to contribute rank that is accumulated from mature domains associated with the immature domains.

[0036]Referring back to ClickHereForSearch.com example, suppose that SearchesRus.com is a new domain that quickly gathered many other domain owners’ attention for its unique search algorithms. Suppose further that popular and/or trusted domains (i.e., mature domains), such as ABC.com, Harvard.edu, and USPS.com, include at least one link to SearchesRus.com in addition to a slew of other new domains. In the present embodiment, a rank for ClickHereForSearch.com may be calculated based not only on the contribution from the mature domains, Yahoo.com, MSN.com, and CNN.com, but also on a rank of SearchesRus.com, which was calculated based only on ranks of its mature contributing domains, ABC.com, Harvard.edu, and USPS.com.

[0037]In further embodiments, instead of identifying each contributing domain as either a mature or immature domain to determine its contribution to a target domain’s rank, each contributing domain’s maturity (e.g., the age of each contributing domain) may be used to determine the extent of the contributing domain’s contribution to the target domain’s rank. In other words, a target domain’s rank may be calculated based in part on a fraction of ranks of contributing domains associated with the domain. The fraction of each contributing domain’s rank used to determine the target domain’s rank corresponds to the maturity (e.g., age) of the contributing domain. For example, in an embodiment, domains that have been registered for more than ten years may contribute 100% of their accumulated ranks to a target domain’s rank; domains that have been registered from six to ten years may contribute 75% of their accumulated ranks to a target domain’s rank; domains that have been registered from three to six years may contribute 50% of their accumulated ranks to a target domain’s rank; domains that have been registered for one to three years may contribute 25% of their accumulated ranks to a target domain’s rank; and domains that have been registered for less than one year may only contribute 10% of their accumulated ranks.

[0038]Referring again to ClickHereForSearch.com example, suppose that Yahoo.com has been registered for more than ten years; CNN.com has been registered for seven years; MSN.com has been registered for four years; and SearchesRus.com has been registered for less than one year. The rank for ClickHereForSearch.com may be calculated based on 100% of the accumulated rank for Yahoo.com, 75% of the accumulated rank for CNN.com, 50% of the accumulated rank for MSN.com, and 10% of the accumulated rank for SearchesRus.com.

Exemplary Methods

[0039]FIG. 4 is a flow diagram illustrating a method 400 for ranking a domain in accordance with an embodiment of the present invention. At block 402, contributing domains associated with a target domain are determined. Typically, the contributing domains are a set of domains that include one or more links to the target domain. As indicated above, in some embodiments, the search engine 208 periodically crawls the source devices, such as the source device 204, and collects new domain information and updates existing domain information. Such information may be used to identify contributing domains associated with the target domain.

[0040]At block 404, the maturity for each of the contributing domains associated with the target domain is determined. In general, a maturity of a domain is determined based on how long the domain has been known to exist. Typically, a maturity of a domain is determined based on the date that the domain was registered or the date that the domain was first discovered by a search engine (e.g., if the registration date cannot be ascertained).

[0041]As indicated above, in some embodiments, one or more of the contributing domains are identified as mature domains based on the maturity of the contributing domains. For example, all domains that were registered more than a year ago may be defined as mature domains. Similarly, in some embodiments, one or more of the contributing domains are determined to be immature domains based on the maturity of the contributing domains. For example, all domains that were registered or discovered for the first time by a search engine less than a year ago may be determined to be immature. In some embodiments, a maturity of a domain is reset if the domain expires or if the domain is swapped. Domain registration is typically based on year-to-year basis. Domain owners are required to pay an annual fee for keeping their domains. Domains will expire if the annual fees are not paid. Expired domains can, thereafter, be purchased by different owners. Spammers may purchase a block of domains that have been expired as well as new domains to form a Web Farm. Domain swapping occurs when domain users trade their domains. Spammers may take advantage of swapping by swapping their domains for domains that have not been tainted. Spammers may be further prevented from escaping preventive measures based on maturity of domains by resetting the maturity of the domains that have expired or have been swapped.

[0042]At block 406, a rank for the target domain is calculated. As indicated above, in some embodiments, only mature contributing domains are used to calculate the rank for the target domain. In other words, only contributing domains that have been identified as mature domains by meeting a predetermined minimum period of existence may contribute to the rank of the target domain. For example, suppose that a spammer purchases one hundred domains and has each of the one hundred domains include links to the remaining ninety nine domains. This extensive interlinking would typically afford each of the one hundred domains a potential to receive a high rank based on the number of domains that include a link thereto even though all one hundred of the domains may be less than a month old. However, the present embodiment prevents these contributing domains that have not been registered for more than a minimum period of time to qualify as mature domains. Accordingly, by not qualifying as mature domains in some embodiments, each of the one hundred spam domains may be successfully stopped from contributing ranks to the remaining ninety nine spam domain accumulating ranks.

[0043]In other embodiments, the target domain’s rank may be determined based on both mature contributing domains and immature contributing domains. However, in such embodiment, immature contributing domains contribute to the target domain’s rank only to the extent that the immature contributing domains have received rank from mature domains associated with the immature domains. For example, suppose that a mature domain is defined as a domain that has been registered for more than six months without being expired or swapped and that a target domain called ChildrensWorld.com is linked to by two other domains, ToysRus.com and NewToyCompany.com. NewToyCompany.com is a new domain that was registered less than a month ago, but is linked to by two mature domains, Kmart.com and Target.com, in addition to other newer domains. A rank for the target domain may be calculated based on a rank of NewToyCompany.com, which was calculated based only on ranks of the two mature contributing domains, Kmart.com and Target.com, in addition to the rank of ToysRus.com, which is a mature domain.

[0044]In further embodiments, the target domain’s rank is determined not by identifying mature and immature contributing domains, but by determining the extent of a contributing domain’s contribution based on its maturity. Such embodiments provide a sliding scale approach based on contributing domain maturity. In such embodiments, a fraction may be determined for each contributing domain based on its maturity and applied to determine that respective contributing domain’s contribution to the target domain’s rank. For example, contributing domains that have been registered for a longer period of time (i.e., have a greater maturity) may contribute more to a target domain’s rank than contributing domains that have been registered for a shorter period of time (i.e., have a lesser maturity).

[0045]FIG. 5 is a flow diagram illustrating a method 500 for presenting search results in accordance with an embodiment of the present invention. At block 502, a search query is received at a search engine, such as the search engine 208 of FIG. 2, from a client device, such as the client device 202 of FIG. 2. At block 504, one or more search results are determined for the search query using domains that have been previously received or collected and stored in a database, such as the database 308 of FIG. 3. For example, the search engine may search the database and select one or more domains stored therein that match the search query.

[0046]At block 506, a search results user interface is generated using domain rankings to determine an order for the search results. For example, the search results may be presented with the higher ranked domains at the top such that users would see more reliable and/or popular domains first. Typically, ranks for the domains have already been determined and stored in the database prior to being used for ordering the search results. The domain rankings may have been generated in a manner similar to the embodiments described hereinabove with reference to FIG. 4. The search result user interface is then communicated from the search engine to the client device for presentation on the client device, as shown at block 508. Advantageously, the present invention’s approaches to ranking domains may be used to assist search engines to rank domains in accordance with the popularity and utility of the domains while preventing spam domains from earning undeservedly high ranks.

CONCLUSION

[0047]Embodiments of the present invention relate to, among other things, ranking a domain. One or more contributing domains associated with a target domain are identified and the maturity of the contributing domains is determined. By way of example only and not limitation, the maturity of a contributing domain may be determined based on the date that it was registered or the date that it was first discovered by a search engine. In turn, the maturity of the contributing domains may be used to calculate a rank for the target domain.

[0048]The present invention has been described in relation to particular embodiments, which are intended in all respects to be illustrative rather than restrictive. Alternative embodiments will become apparent to those of ordinary skill in the art to which the present invention pertains without departing from its scope.

[0049]From the foregoing, it will be seen that this invention is one well adapted to attain all the ends and objects set forth above, together with other advantages which are obvious and inherent to the system and method. It will be understood that certain features and subcombinations are of utility and may be employed without reference to other features and subcombinations. This is contemplated by and is within the scope of the claims.

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Desktoptopia is a cool app for the mac that loads designer desktops on your monitor from an ever growing database of top creative desktops. www.desktoptopia.com

http://spambox.us/ lets you set the expire date of your temporary email address from 30 minutes, to a whole year

In addition to my last post, http://www.youconvertit.com/ lets you convert files up to 300Mb in size, instead of media-convert’s 150Mb and zamzar’s 100Mb. It also lets you convert up to 5 files at once.

dontreg.com – temp email is useful too.

Wiki tools Zoho to the list. It provides around 14 different tools like wiki to CRM tools, chat and may more.

Regarding security and mail delivery, I suggest this very interesting service: https://lockbin.com/

It’s very useful, reliable and easy-to-use. A big help ensuring your privacy online.

There are more free DNS, IP and host tools at mydnstools.info, including a very cool web host / webserver info tool.

Here is a list that has hundreds of free ware ranked by popularity

http://michaeleee.blogspot.com/2007/01/list-of-best-freeware.html

I find FreeTube useful when theres some news event thing happening that I want to learn more on..it shows live television channels mostly news rather entertaining.

Del.icio.us is a social bookmarking site that allows you to bookmark sites and view them from any computer. This site is great because not only can you bookmark sites and view them anywhere, you can also search through everyone’s bookmarks to find great tech articles.

Omnidrive is an online storage service that allows you to upload large files, access them from any computer, and share them with other people. They also offer the ability to edit your Office documents using Zoho without ever downloading them. You get 1GB free and the ability to upgrade to 1 terabyte. This site is great for hosting your tech tools and accessing them from computers you are working on.

10 Minute Mail allows you to create temporary email addresses that expire after 10 minutes. It’s great to use for sites that require you to receive something through email but you don’t want to be bombarded with spam.

Free Password Generator
Free Password Generator generates very strong and unique passwords. Before you generate your passwords, you can predefine settings such has what type of symbols to use and the length you want it to be.

Trend Micro HouseCall is an online virus, spyware, and malware scanner that runs in your web browser. It’s very handy when you are working on a computer that doesn’t have antivirus software and you want to scan it without having to install one.

You Get Signal allows you to check which ports are open into your network. This is great tool to use when you are trying to patch holes in your firewall.

WhatIsThatFile.com
WhatIsThatFile.com allows you to identify unknown files on a computer. This tool is great for looking up files that you suspect might be possible viruses, trojans, or malware.

YouSendIt allows you to send large files to other people when the files are too large for your email. This tool is a great alternative to using FTP.

DLL-files.com has a huge library of downloadable dll files. Next time you get an error about a missing dll file, you can go here and download it.

Google Microsoft Search allows you to search specifically through Microsoft-related sites. This site is great for searching through Microsoft tech articles for a specific problem.

Zamzar is a file conversion tool that allows you to convert file types through their site. Currently they support over 60 file types. This is a great tool for converting files when you don’t have the appropriate application to do so. make sure your pop up blocker is turned on!

Default Router Passwords Database allows you to search for router as well as other devices default passwords. This tool comes in very handy when you have to reset a device but can’t find the manual to look up the default password.

SMO, or Social Media Optimization, helps build website traffic by using social media based websites. The dawning of web 2.0 has seen many different social media websites crop up in an equally large number of different guises. Content sharing, social bookmarking, and collaborative websites form the basis of this initiative and it is these types of website that you need to use in order to leverage the power of the social web.

Myth #1: The Higher Your Google PageRank (PR), the Higher You’ll be in the Search Results Listing – PageRank has nothing to do with the ranking of web pages, it has to do with the level of authoritativeness the page has and how often it will be reindexed. Higher PageRank pages tend to be reindexed more often.

Myth #2: The Google Toolbar will List Your Actual PageRank – The toolbar displays PageRank and back link information that is generally 3-5 months old.

Myth # 3: PageRank is a Value Based on the Number of Incoming Links to Your Site – It is more to do with the QUALITY of the links coming into your site.

Myth # 4: Searching for Incoming Links on Google Using “link:” will Show you all Your BackLinks – Google only shows you a small number of the links they know about. They have publicly stated that the links they show you may not all be counted towards PageRank. Instead, use Yahoo! or MSN as a gauge to your link progress.

Myth #5: Being Listed in the Open Directory Project Gives you a Special PageRank Bonus – There is not a “special” bonus, you get PageRank from the ODP the same as you would from any other site. No special treatment is given.

Myth #6: Being Listed in Yahoo! Gives you a Special PageRank Bonus – See #5. There is no special bonus given.

Myth #7: Google Analytics is used to track your user behavior for future products with Google – The data is not used by Google per the terms of use. There is no real value for Google to analyze that information, unless Yahoo! or MSN decided to use Google Analytics.

Myth #8: Google Will Not Index Dynamic Pages – Google indexed dynamic content all the time, the issue is, does it index it correctly, and that is the responsibility of the web master, not Google.

Myth # 9: Google Will Not List Your Site, or Penalize it, if you use Pop-ups – Google does not view pop-ups as an indexing problem. However, if the pop-ups are abusive, you can be manually de-indexed.

Myth # 10: Google will Penalize you if You’re Linked to by a Link Farm – While Google has stated that you cannot be penalized because of something that is not in your direct control, they do have systems in place to determine if you are participating in programs which are against their terms of use.

WordPress SEO Tip #20  Don’t Block the Search Engines!

First and foremost: make sure you’re not inadvertently telling the search engines to go away! Believe it or not, some WordPress installations block the search engine bots by default.

From your admin panel, go to Options > Privacy and make sure its set to I would like my blog to be visible to everyone.
Bonus Tip #1 – Are Comments Enabled?

Some WordPress users restrict comments to registered users, or disable them entirely. While this may be appropriate in some situations, in most cases comments are a very beneficial factor, and a defining mark, of a blog.

Comments engage your readers, help you get more fresh content SEO brownie points, and give search engines another reason to come back frequently.

Here’s how to fully enable comments:

1. Login to the WordPress administration center
2. Click Options on the menu bar
3. Is Users must be registered and logged in to comment checked? If so, consider unchecking it.
4. Click Discussion on the submenu bar
5. Make sure the following are checked: Allow people to post comments on the article and Allow link notifications from other Weblogs (pingbacks and trackbacks.)

WordPress SEO Tip #19  Does Your Blog Have a Topic?

Some of us would prefer to have a blog where we talk about anything that comes to mind: cars, movies, photosynthesis, dust mites, you name it.

In and of itself, such a blogging style isnt wrong; however, you can leave search engines clueless as to what your blogs about and thus for what search queries your blog should appear. And some of your readers might get annoyed in the process as well.
WordPress SEO Tip #18  Ensure URL Canonicalization

If your blog posts are accessible from more than one URL, you could end up with:

* Search engines confused as to which URL to display in the SERPs.
* PageRank split between multiple pages.
* Duplicate content penalties.

Starting with version 2.3, WordPress takes care of this and makes sure your content is accessible from only one place. So if you use an older version, either upgrade to the latest version of WordPress.
WordPress SEO Tip #17  Check for Valid XHTML

Most code errors are minor, but the more serious ones can cause content misinterpretation by search engines, lower rankings, and rendering errors.

WordPress itself produces valid code, but errors can crop up from two other common sources:

* Poorly written plugins or themes
* User-created coding errors (in the blog posts themselves, or through theme customizations)

First check your site for errors. If an error is found, look at the surrounding content to determine the source of the error.

If a plugin is the culprit, fix it if you’re good at that sort of thing (the beauty of open source!), or send a quick email to the plugin developer and let him or her know.
WordPress SEO Tip #16 – Don’t Leech Link Juice!

One characteristic of WordPress blogs is the sidebar, which is typically present on every single page. Do you really need to be passing link juice from every single one of your pages to every single one of those links? If the answer is no, consider adding rel=nofollow to the less important ones.
WordPress SEO Tip #15  Use Images in Your Posts

Not only do they increase visitor attention and retention, they give you an opportunity to use keyword-rich alt attributes, title attributes, and filenames. Plus it’ll give your blog visibility in image search engines.
WordPress SEO Tip #14  Does Your Theme Use Header Tags Correctly?

* The blog title, or your main keyword should be in an <h1> tag.
* If your subtitle is keyword-rich, you can put it in an <h2>; otherwise I recommend putting it in a non-header tag like <div>.
* The post titles should go in <h2> tags.
* Sidebar section titles should be <h3> tag or non-header.

Unfortunately, some themes (including the WordPress Default Theme) put the sidebar section titles in <h2> tags. Although this makes sense from a strict structural point of view, it also gives irrelevant sidebar headers (Categories, Archives, Meta, etc.) equal weight with your SEO-important post titles.

To sum it up: Use a theme that utilizes header-tags properly, or try fixing the theme you have.
WordPress SEO Tip #13  Use Pinging

A ping is a this site has new content notification that invites bots to visit your blog.

WordPress pings one website called Ping-o-matic by default, which in turn pings others. You can also add additional services by going to Options > Writing in the admin panel. (For example, the pinging URL for Google Blog Search is http://blogsearch.google.com/ping/RPC2)

Another Bonus Tip: Once a post is published, WordPress issues pings whenever the post is edited. Try to cut down on after-publishing edits to avoid being considered a ping spammer.
WordPress SEO Tip #12  Install the Google XML Sitemaps Generator Plugin

XML Sitemaps are search-engine-friendly directories of your blogs posts and other pages intended to help search engines spider your site. Though pioneered by Google, theyre supported by Yahoo, MSN, and Ask.com as well.

The Google XML Sitemaps Generator for WordPress makes creation of these sitemaps easy and automatic. It also lets the engines know when you post new content.
WordPress SEO Tip #11  Avoid Sponsored Themes

There was a debate in the WordPress community not too long ago on the topic of sponsered themes. These themes include paid links (usually in the footer) than can suck PageRank and possibly result in a Google paid links penalty.

Stick with WordPress theme directories that dont include sponsored themes, like the WordPress Theme Viewer.
Bonus Tip #2  Write Right Post Titles

SEO isnt everything: once youre high in the SERPs, you need action words to prompt clickthroughs.

Put keywords in your title if at all possible, but not if it’ll compromise the click-trigger action title.
WordPress SEO Tip #10  Use Traditional SEO Techniques

A WordPress blog is a website too, so the traditional SEO techniques still apply:

* Use important keywords in the title and throughout the post, but don’t overdo it.
* Bold your keywords when it makes sense.
* Develop links to your blog.

WordPress SEO Tip #9  Use the Power of the Slug

Ever wondered what the Post Slug on the Write page was? Its the text that goes in the URL when you have Pretty Permalinks enabled (see tip #2).

By default the slug is a sanitized version of the post title. However, if your title is overly long or keyword-sparse, you can change the slug through the Post Slug box.

Yet Another Bonus Tip: The SEO Slugs plugin can take out common words like you, is, etc. out of the slug for you automatically.
WordPress SEO Tip #8  Use Timestamping to Stagger Fresh Content

Search engines and visitors love fresh blog content on a steady, regular basis. But for a lot of us, creativity comes irregularly: 10 post ideas one week, none the next.

Enter timestamping. When writing a post, click the plus sign next to Post Timestamp. Set a date and time, and the post will publish by itself whenever you specify.

Search engines will keep coming back, and visitors wont be inundated with a ton of new posts all at once.

Hint: If youve timestamped a post, dont click the Publish button, since thatll publish your post immediately regardless of your timestamp. Instead, select Published under Post Status and click the Save button.
WordPress SEO Tip #7  Use Tags for Free Keyword Boosts

WordPress 2.3 and above include a tags feature that lets you assign keywords to your blog posts. Once you start using them, then since each tag gets its own webpage, youll be generating a ton of your own themed, keyword-oriented internal backlink pages.
WordPress SEO Tip #6  Integrate Social Media

Adding social media links/buttons like the ones above makes it easy for visitors to promote your quality content (hint, hint). Social media is a great way to build links naturally as well as drive targeted site traffic.

* Share This is a very popular social media all-in-one plugin.
* If youre a FeedBurner user, you can use FeedFlare to add action links, including social media ones, to the bottom of your posts.

Lots of social media sites provide code you can use to generate buttons like those above. Grab your own code from:

* Digg
* Sphinn
* StumbleUpon
* Mixx
* Scoop

WordPress SEO Tip #5  Implement Deep-Linking

Here are several great ways to implement deep-linking on your WordPress blog:

* Within your posts, link to other posts on your blog and use important keywords in the anchor text.
* Install the Similar Posts plugin, which inserts a list of related posts youve written to the bottom of each of your blog posts. This process will create aged deep links and increase visitor retention.
* Display your most popular posts in your sidebar using the Popularity Contest plugin. Gives your most popular posts tons of internal links, and helps your visitors find your best content.

WordPress SEO Tip #4  Make Scrapers Work to Your Advantage

Most of us would probably be upset if someone used scraping (automated content stealing) to publish our laboriously-written posts as his or her own.

But with a little work, you can make the scrapers work for you, not against you.

Heres how to do it, courtesy of EarnersBlog.com:

If you use WordPress its very easy to take full advantage of these sites linking to you, all you need to do is create links back to your content within your feed.

What youll need for this:

* Cave Monkeys Full Text Feed Plugin
* Solo Technologies Add Related Posts to your Feed Plugin

These plugins simply show your entire post in your feed & also add some related posts in your feed only (which will also increase the amount of people in your feed reading more than 1 post).
Now, everytime anyone scrapes your blog via your RSS feed & republishes it theyll be deep linking to 5 or more of your existing posts. Bingo.

WordPress SEO Tip #3  Install the All-in-One SEO Plugin

Like the name implies, this plugin covers a lot of the bases.

* Puts the blog name after the post title, giving your keyword-rich titles more prominence.
* Allows you to override title and meta tags on your homepage as well as your individual posts.
* Lets you add noindex to your category and/or tag pages to avoid duplicate content.
* And more.

A must-have for serious WordPress SEO.
WordPress SEO Tip #2  Use Pretty Permalinks

Sure, you may already use Pretty Permalinks, but are you using the best possible permalink structure?

For those of who dont use Pretty Permalinks, its a must-do for WordPress SEO. Permalinks, in essence, are the URLs of your WordPress blog posts. Pretty Permalinks put slugs (which should contain keywords  see tip #9) in your URLs instead of the default numbers.

To enable or change them, first login, then go to Options > Permalinks.

The two options you do not want are Default and Numeric. Here are my suggestions for picking a pretty permalink structure:

* Date and Name Based: The problem with this is that your posts are several extra directories deep, which can decrease relevence in some search engines. However, such a permalink structure can nevertheless be desireable if your blog is news-oriented or date-sensitive.
* Post Name Only: If your blog covers one topic that has no subtopics (which, though possible, is unlikely), select Custom and type /%postname%/
* Category Based: If your blog covers multiple topics, implement category-based URLs. (You have to look into the Codex to find information on category-based URLs, so many WordPress users probably dont realize that this option exists!) To implement it, select Custom and type /%category%/%postname%/

WordPress SEO Tip #1  WordPress Secret: Use Category-Based Permalinks for SEO Siloing

Heres the big finale. Problem is, this tip is so important (and lengthy) that it really merits its own post.

Heres a teaser: it entails implementing the powerful siloing technique on your WordPress blog through a combination of plugins, settings, and strategies.
Conclusion

Okay, so it was actually more like 23+ tips instead of 20. I certainly hope you gleaned a useful strategy or two in your quest for WordPress search engine optimization. If you enjoyed this post, please social it, email it, link it, or leave a comment!