APPLICATION REPRESENTATION FOR APPLICATION EDITIONS

• US 20130290318A1
• Filed: 03/15/2013
• Published: 10/31/2013
• Est. Priority Date: 04/26/2012
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Liron Shapira, Nicolas Tarleton
• Inventors: SHAPIRA, LIRON, KAGAN, TOMER, TARLETON, NICOLAS
• Granted Patent: US 9,201,946 B2
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/2455 Query execution
• CPC Class Codes: G06F 16/24553 of query operations
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/4387 by the use of playlists
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

A disclosed system, method, and computer-readable storage medium automatically identify, cluster, and cross-reference various editions of an application. The editions are clustered and associated with a canonical application structure describing the general functionality of each edition in the cluster. When an application search query is received from a client device, one or more canonical applications corresponding to the query are identified and provided to the client device. Enhancing the relevancy of search results by merging several editions of an application into one canonical application structure reduces unwanted and redundant results on a search result page.

Claims

1. A computer-implemented method comprising:

aggregating application data from one or more data sources;

identifying application editions and description information corresponding to the application editions based on the aggregated application data;

clustering the application editions to generate one or more clusters of application editions, wherein the clustering is based at least in part on the description information associated with each application edition, and wherein each cluster includes a set of application editions determined to be similar to one another; and

associating, for each cluster, the set of application editions in the cluster to a canonical application;

receiving an application search query from a client device;

identifying one or more canonical applications based on the application search query, wherein each canonical application is identified based at least in part on description information corresponding to the set of application editions associated with the canonical application;

ranking the identified one or more canonical applications to generate a ranked list of application recommendations, wherein the ranking is based at least in part on the description information corresponding to the application editions associated with the canonical applications; and

providing the ranked list of application search results to the client device, wherein each result in the list indicates a canonical application and one or more application editions associated with the canonical application.

2. The method of claim 1, further comprising:

generating one or more indexes based at least in part on the description information corresponding to the set of application editions associated with the canonical application;

wherein the set of application editions is stored in the one or more indexes in relation to the canonical application.

3. The method of claim 1, further comprising:

aggregating the description information corresponding to each application edition associated with the canonical application; and

generating a generic description corresponding to the canonical application based on the aggregated description information.

4. The method of claim 3, further comprising:

identifying another application edition based on the application data;

associating the other application edition with a cluster; and

updating the generic description corresponding to the canonical application of the cluster based on description information associated with the other application edition.

5. The method of claim 1, wherein clustering the application editions comprises executing one or more heuristics.

6. A non-transitory computer-readable storage medium storing computer program instructions executable to perform steps comprising:

aggregating application data from one or more data sources;

identifying application editions and description information corresponding to the application editions based on the aggregated application data;

clustering the application editions to generate one or more clusters of application editions, wherein the clustering is based at least in part on the description information associated with each application edition, and wherein each cluster includes a set of application editions determined to be similar to one another;

associating, for each cluster, the set of application editions in the cluster to a canonical application;

receiving an application search query from a client device;

responsive to receiving the application search query, identifying one or more canonical applications based on the application search query, wherein each canonical application is identified based at least in part on description information corresponding to the set of application editions associated with the canonical application;

ranking the identified one or more canonical applications to generate a ranked list of application recommendations, wherein the ranking is based at least in part on the description information corresponding to the sets of application editions associated with the canonical applications; and

providing the ranked list of application search results to the client device, wherein each result in the list indicates a canonical application and one or more application editions associated with the canonical application.

7. The computer-readable storage medium of claim 6, the steps further comprising:

generating one or more indexes based at least in part on the description information corresponding to the set of application editions associated with the canonical application;

wherein the set of application editions is stored in the one or more indexes in relation to the canonical application.

8. The computer-readable storage medium of claim 6, the steps further comprising:

aggregating the description information corresponding to each application edition in the set of application editions associated with the canonical application; and

generating a generic description corresponding to the canonical application based on the aggregated description information.

9. The computer-readable storage medium of claim 8, the steps further comprising updating the description information corresponding to each application edition based on the generic description corresponding to the canonical application.

10. The computer-readable storage medium of claim 6, wherein clustering the application editions comprises executing one or more heuristics.

11. A system comprising:

a non-transitory computer-readable storage medium storing executable computer program instructions comprising instructions for;

aggregating application data from one or more data sources;

identifying one or more application editions and description information corresponding to the one or more application editions based on the aggregated application data;

clustering the one or more application editions to generate one or more clusters of application editions, wherein the clustering is based at least in part on the description information associated with the application editions, and wherein each cluster includes a set of application editions determined to be similar to one another;

associating, for each cluster of application editions, the set of application editions in the cluster to a canonical application;

receiving an application search query from a client device;

responsive to receiving the application search query, identifying one or more canonical applications based on the application search query, wherein each canonical application is identified based at least in part on description information corresponding to the set of application editions associated with the canonical application;

ranking the identified one or more canonical applications to generate a ranked list of application recommendations, wherein the ranking is based at least in part on the description information corresponding to the sets of application editions associated with the canonical applications; and

providing the ranked list of application search results to the client device, wherein each result in the list indicates a canonical application and one or more application editions associated with the canonical application; and

a processor for executing the computer program instructions.

12. The system of claim 11, the instructions further comprising:

generating one or more indexes based at least in part on the description information corresponding to the set of application editions associated with the canonical application;

wherein the set of application editions is stored in the one or more indexes in relation to the canonical application.

13. The system of claim 11, the instructions further comprising:

aggregating the description information corresponding to each application edition in the set of application editions associated with the canonical application; and

generating a generic description corresponding to the canonical application based on the aggregated description information.

14. The system of claim 13, the instructions further comprising updating the description information corresponding to each application edition based on the generic description corresponding to the canonical application.

15. The system of claim 11, wherein clustering the application editions comprises executing one or more heuristics.

16. A computer-implemented method comprising:

aggregating application data from one or more data sources;

identifying application editions and description information corresponding to the application editions based on the aggregated application data;

clustering the application editions to generate one or more clusters of application editions, wherein the clustering is based at least in part on the description information associated with each application edition, and wherein each cluster includes a set of application editions determined to be similar to one another; and

associating, for each cluster, the set of application editions in the cluster to a canonical application.

17. The method of claim 16, further comprising:

generating one or more indexes based at least in part on the description information corresponding to the set of application editions associated with the canonical application;

wherein the set of application editions is stored in the one or more indexes in relation to the canonical application.

18. The method of claim 16, further comprising:

aggregating the description information corresponding to each application edition in the set of application editions associated with the canonical application; and

generating a generic description corresponding to the canonical application based on the aggregated description information.

19. The method of claim 18, further comprising updating the description information corresponding to each application edition based on the generic description corresponding to the canonical application.

20. The method of claim 16, wherein clustering the application editions comprises executing one or more heuristics.

21. A computer-implemented method comprising:

receiving an application search query at a client device;

transmitting the application search query to an application search system, the application search system configured to identify one or more canonical applications based on the application search query, wherein each canonical application is associated with one or more application editions determined to be similar to one another;

receiving an identifier of each of the canonical applications and the application editions associated with each canonical application from the application search system;

displaying, by the client device, a results list including the identifiers of the canonical applications;

receiving a user selection of an identifier in the results list; and

responsive to receiving the user selection, displaying the identifiers of each application edition associated with the canonical application corresponding to the selected identifier.

22. The method of claim 21, wherein the identifier of each canonical application and application edition includes an image, and wherein the method further comprises:

selecting the image for display with each canonical application identifier based on images corresponding to the application editions associated with each canonical application.