DYNAMICALLY DETERMINING THE RELATEDNESS OF WEB OBJECTS

• US 20120284266A1
• Filed: 05/04/2011
• Published: 11/08/2012
• Est. Priority Date: 05/04/2011
• Status: Active Grant

• Current Assignee: Yahoo Assets LLC
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Sanyal, Subhajit, Sathish, Sriram J., CHANDRAGHATGI, Prateeksha Uday
• Granted Patent: US 9,262,518 B2
• Time in Patent Office: Days
• US Class Current: 707/737
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: G06F 16/43 Querying
• CPC Class Codes: G06F 16/483 using metadata automatically derived from the content
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06Q 30/0277 Online advertisement

Abstract

A first cluster of web objects is identified from a click-through data structure. The click-through data structure can organize web objects into clusters based on query results of web objects selected by a user. Also, a second cluster of web objects can be identified from a metadata data structure. The metadata data structure can organize web objects into clusters based on metadata associated with the web objects. An output set of web objects is selected, in real time, from the identifier clusters.

Claims

1. A computer-implemented method for dynamically determining the relatedness of web objects, comprising:

receiving a new web object;

identifying a first cluster of web objects from a first data structure comprising web objects that are organized into clusters based on a click-through relatedness;

identifying a second cluster of web objects from a second data structure comprising web objects that are organized into clusters based on a metadata relatedness; and

selecting, in real time, an output set of web objects related to the new web object from the first and second clusters of web objects.

2. The method of claim 1, further comprising:

identifying one or more clusters based on metadata associated with the new web object.

3. The method of claim 2, wherein the one or more clusters includes the first set of web objects based on a click-through relatedness.

4. The method of claim 2, wherein the one or more clusters includes the second set of web objects based on metadata relatedness.

5. The method of claim 2, further comprising:

calculating a relatedness between the new web object and the one or more clusters using a weighted cosine distance, the relatedness comparing metadata of the new web object against metadata of the one or more clusters.

6. The method of claim 2, wherein the metadata comprises at least one or a search term, a category, and a description of the new web object.

7. The method of claim 1, wherein the web objects comprises at least one or a video, an image, and a document.

8. The method of claim 1, further comprising:

generating clusters from a plurality of web objects, each cluster based on a relatedness of a set of web objects.

9. The method of claim 1, further comprising:

adding the new web object to the first and second data structures during batch processing.

10. A computer program product stored on a non-transitory computer-readable medium that when executed by a processor, performs a method for dynamically determining the relatedness of web objects, comprising:

receiving a new web object;

identifying a first cluster of web objects from a first data structure comprising web objects that are organized into clusters based on a click-through relatedness;

identifying a second cluster of web objects from a second data structure comprising web objects that are organized into clusters based on a metadata relatedness; and

selecting, in real time, an output set of web objects related to the new web object from the first and second clusters of web objects.

11. The computer program product of claim 10, further comprising:

identifying one or more clusters based on metadata associated with the new web object.

12. The computer program product of claim 11, wherein the one or more clusters includes the first set of web objects based on a click-through relatedness.

13. The computer program product of claim 11, wherein the one or more clusters includes the second set of web objects based on a metadata relatedness.

14. The computer program product of claim 11, further comprising:

calculating a relatedness between the new web object and the one or more clusters using a weighted cosine distance, the relatedness comparing metadata of the new web object against metadata of the one or more clusters.

15. The computer program product of claim 11, wherein the metadata comprises at least one or a search term, a category, and a description of the new web object.

16. The computer program product of claim 10, wherein the web objects comprises at least one or a video, an image, and a document.

17. The computer program product of claim 10, further comprising:

generating clusters from a plurality of web objects, each cluster based on a relatedness of a set of web objects.

18. The computer program product of claim 10, further comprising:

adding the new web object to the first and second data structures during batch processing

19. A computer system, at least partially implemented in hardware, for dynamically determining the relatedness of web objects, comprising:

a client communication module, in the computer system, to receive an indication of a new web object;

a cluster identifier, communicatively coupled to the client communication module, the cluster identifier identifying a first cluster of web objects from a first data structure stored in a database and comprising web objects that are organized into clusters based on a click-through relatedness, the cluster identifier identifying a second cluster of web objects from a second data structure stored in the database and comprising web objects that are organized into clusters based on a metadata relatedness; and

an object selector, communicatively coupled to the cluster identifier, the object selector selecting in real time an output set of web objects related to the new web object from the first and second clusters of web objects.

20. The system of claim 19, wherein the cluster identifier identifies one or more clusters based on metadata associated with the new web object.