Application representation for application editions

• US 9,201,946 B2
• Filed: 03/15/2013
• Issued: 12/01/2015
• Est. Priority Date: 04/26/2012
• Status: Expired due to Fees

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Quixey, Inc.
• Inventors: Shapira, Liron, Kagan, Tomer, Tarleton, Nicolas
• Primary Examiner(s): Lu, Charles
• Application Number:
  US13/840,727
• Publication Number:
  US 20130290318A1
• Time in Patent Office: 991 Days
• Field of Search: 707/740
• US Class Current: 1/1
• 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 different application editions and description information corresponding to the different 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

for each cluster;

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

generating a canonical application structure based on the canonical application associated with the cluster and the one or more application editions in the cluster, the canonical application structure indicating the canonical application and the application editions, wherein the canonical application structure includes general attributes attributed to the canonical application and edition attributes that are specific to a respective application edition; and

for each application edition, determining a platform for which the application edition is configured from the application data corresponding to the application edition and updating the edition attributes corresponding to the application edition to indicate the platform;

receiving an application search query from a client device and a platform constraint indicating a specific platform;

identifying one or more canonical applications based on the application search query and the platform constraint, 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 and the platforms respectively indicated by the edition attributes thereof;

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. The method of claim 1, wherein identifying one or more canonical applications based on the application search query and the platform constraint includes querying a platform specific search index based on the search query, the platform specific search index corresponding to the specific platform indicated in the platform constraint and outputting one or more canonical application structures respectively representing the one or more canonical applications.

7. 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;

for each cluster;

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

generating a canonical application structure based on the canonical application associated with the cluster and the one or more application editions in the cluster, the canonical application structure indicating the canonical application and the application editions, wherein the canonical application structure includes general attributes attributed to the canonical application and edition attributes that are specific to a respective application edition; and

for each application edition, determining a platform for which the application edition is configured from the application data corresponding to the application edition and updating the edition attributes corresponding to the application edition to indicate the platform;

receiving an application search query and a platform constraint indicating a specific platform from a client device;

responsive to receiving the application search query, identifying one or more canonical applications based on the application search query and the platform constraint, 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 and the platforms respectively indicated by the edition attributes thereof;

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.

8. The computer-readable storage medium of claim 7, 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.

9. The computer-readable storage medium of claim 7, 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.

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

11. The computer-readable storage medium of claim 7, wherein clustering the application editions comprises executing one or more heuristics.

12. The computer-readable storage medium of claim 7, wherein identifying one or more canonical applications based on the application search query and the platform constraint includes querying a platform specific search index based on the search query, the platform specific search index corresponding to the specific platform indicated in the platform constraint and outputting one or more canonical application structures respectively representing the one or more canonical applications.

13. 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;

for each cluster;

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

generating a canonical application structure based on the canonical application associated with the cluster and the one or more application editions in the cluster, the canonical application structure indicating the canonical application and the application editions, wherein the canonical application structure includes general attributes attributed to the canonical application and edition attributes that are specific to a respective application edition; and

for each application edition, determining a platform for which the application edition is configured from the application data corresponding to the application edition and updating the edition attributes corresponding to the application edition to indicate the platform;

receiving an application search query and a platform constraint from a client device, the platform constraint indicating a specific platform of the client device;

responsive to receiving the application search query, identifying one or more canonical applications based on the application search query and the platform constraint, 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 and the platforms respectively indicated by the edition attributes thereof;

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.

14. The system of claim 13, 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.

15. The system of claim 13, 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.

16. The system of claim 15, the instructions further comprising updating the description information corresponding to each application edition based on the generic description corresponding to the canonical application.

17. The system of claim 13, wherein clustering the application editions comprises executing one or more heuristics.

18. The system of claim 13, wherein identifying one or more canonical applications based on the application search query and the platform constraint includes querying a platform specific search index based on the search query, the platform specific search index corresponding to the specific platform indicated in the platform constraint and outputting one or more canonical application structures respectively representing the one or more canonical applications.