MINING BROAD HIDDEN QUERY ASPECTS FROM USER SEARCH SESSIONS

• US 20100145944A1
• Filed: 12/10/2008
• Published: 06/10/2010
• Est. Priority Date: 12/10/2008
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: WANG, Xuanhui, CHAKRABARTI, Deepayan, PUNERA, Kunal
• Granted Patent: US 9,305,051 B2
• Time in Patent Office: Days
• US Class Current: 707/736
• CPC Class Codes: G06F 16/2425 Iterative querying; Query formulation based on the results of a preceding query
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

An optimization-based framework is utilized to extract broad query aspects from query reformulations performed by users in historical user session logs. Objective functions are optimized to yield query aspects. At run-time, the best broad but unspecified query aspects relevant to any user query are presented along with the results of the run time query.

Claims

1. A computer-implemented method for providing search results, comprising:

analyzing search logs for query reformulations;

extracting query reformulations from the analysis of the search logs;

clustering the extracted query reformulations into clusters;

selecting a group of the clustered extracted query reformulations;

selecting clustered query reformulations from among the group of clustered extracted query reformulations so as to maximize a similarity measure; and

presenting the clustered extracted query reformulations along with the results of a search.

2. The method of claim 1, wherein clustering comprises modified star clustering.

3. The method of claim 1, wherein selecting the group of clustered extracted query reformulations comprises selecting x clustered extracted query reformulations, wherein:

50<

x<

150.

4. The method of claim 1, further comprising determining if the number of views of a page associated with the extracted query reformulations exceeds a threshold value within a given time period.

5. The method of claim 1, wherein each query reformulation comprises an initial query and a subsequent modifier added to the initial query.

6. A computer-implemented method for providing search results, comprising:

analyzing search logs for (i) a first query by a user comprising a first search term, followed by (ii) a second query comprising the first search term and a qualifier not initially specified in the first query;

determining k aspects of the qualifier;

receiving an original query at run time; and

presenting to the user in response to the original query at least one of the k aspects along with results of the original query.

7. The method of claim 6, wherein determining k aspects of the qualifier comprises clustering the first search term and qualifier.

8. The method of claim 7, wherein determining k aspects of the qualifier further comprises selecting from clusters resulting from the clustering.

9. The method of claim 7, wherein clustering comprises modified star clustering.

10. The method of claim 7, wherein clustering comprises k means clustering.

11. The method of claim 7, wherein determining k aspects of the qualifier further comprises an inter cluster move of an aspect from a first cluster to a second cluster.

12. A computerized searching system configured to:

analyze search logs for (i) a first query by a user comprising a first search term, followed by (ii) a second query comprising the first search term and a qualifier not initially specified in the first query;

determine k aspects of the qualifier;

receive an original query at run time; and

present to the user in response to the original query at least one of the k aspects along with results of the original query.