SEARCH PREDICTION USING CONTEXT MODELING

• US 20110295824A1
• Filed: 05/31/2010
• Published: 12/01/2011
• Est. Priority Date: 05/31/2010
• Status: Active Grant

• Current Assignee: Red Hat, Inc. (International Business Machines Corporation)
• Original Assignee: Red Hat, Inc. (International Business Machines Corporation)
• Inventors: Schneider, James Paul
• Granted Patent: US 8,892,590 B2
• Time in Patent Office: Days
• US Class Current: 707/706
• CPC Class Codes: G06F 16/2452 Query translation
• CPC Class Codes: G06F 16/2453 Query optimisation
• CPC Class Codes: G06F 16/3322 using system suggestions G06F16/3325 takes precedence
• CPC Class Codes: G06F 16/9032 Query formulation
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06N 5/04 Inference or reasoning models

Abstract

A method and apparatus for predicting search queries for a user on a search-based system is described. A search engine tracks search queries from a user received at the search engine. A prediction engine compares a search query history from the user with search query histories from other users on the search engine. The search query histories are stored in a storage device of the search-based system. A prediction of a search query for the user is generated based on the comparison. Search query histories from other users having greater similarities with the search query history from the user have a greater computation weight than search query histories from other users with less similarities with the search query history from the user.

Claims

1. A computer-implemented method comprising:

tracking search queries from a user received at a search engine of a search-based system;

comparing a search query history from the user with search query histories from other users on the search engine, the search query histories stored in a storage device accessible to the search-based system; and

generating a prediction of a search query for the user based on the comparison, search query histories from other users having greater similarities with the search query history from the user have a greater computation weight than search query histories from other users with less similarities with the search query history from the user.

2. The method of claim 1 wherein tracking further comprises:

storing a history of search queries from the user in the storage device.

3. The method of claim 1 wherein generating further comprises:

determining the number of common search queries between the search history of the user and the search history of each other user;

associating the search query history of the user with the search query of at least one other user having the most number of common search queries;

determining where a test sequence of the search history of the user is most similar to a reference sequence from at least one other user having the most number of common search queries; and

determining a new search query for the user from the search query history of at least one other user having the most number of common search queries based on the test sequence and the reference sequence.

4. The method of claim 1 wherein generating further comprises:

determining the number of common search queries between the search history of the user and the search history of other users;

associating the search query history of the user with the search query of at least another user having a minimum threshold of search queries similarities;

determining where a test sequence of the search history of the user is most similar to a reference sequence from at least another user having the minimum threshold of search queries similarities; and

determining a new search query for the user from the search query history of at least another user having the minimum threshold of search queries similarities based on the test sequence and the reference sequence.

5. The method of claim 1 wherein the computation weight is adjusted based on the search histories from other users.

6. The method of claim 1 further comprising:

caching the search results from a predicted search queries prior to selection of the search query by the user.

7. The method of claim 1 wherein search queries from the user comprise orders placed by the user on the search-based system based on the results of the search queries.

8. A computer-readable storage medium, having instructions stored therein, which when executed, cause a computer system to perform a method comprising:

tracking search queries from a user received at a search engine of a search-based system;

comparing a search query history from the user with search query histories from other users on the search engine, the search query histories stored in a storage device accessible to the search-based system; and

generating a prediction of a search query for the user based on the comparison, search query histories from other users having greater similarities with the search query history from the user have a greater computation weight than search query histories from other users with less similarities with the search query history from the user.

9. The computer-readable storage medium of claim 8 wherein tracking further comprises:

storing a history of search queries from the user in the storage device.

10. The computer-readable storage medium of claim 8 wherein generating further comprises:

determining the number of common search queries between the search history of the user and the search history of each other user;

associating the search query history of the user with the search query of at least one other user having the most number of common search queries;

determining where a test sequence of the search history of the user is most similar to a reference sequence from at least one other user having the most number of common search queries; and

determining a new search query for the user from the search query history of at least one other user having the most number of common search queries based on the test sequence and the reference sequence.

11. The computer-readable storage medium of claim 8 wherein generating further comprises:

determining the number of common search queries between the search history of the user and the search history of other users;

associating the search query history of the user with the search query of at least another user having a minimum threshold of search queries similarities;

determining where a test sequence of the search history of the user is most similar to a reference sequence from at least another user having the minimum threshold of search queries similarities; and

determining a new search query for the user from the search query history of at least another user having the minimum threshold of search queries similarities based on the test sequence and the reference sequence.

12. The computer-readable storage medium of claim 8 wherein the computation weight is adjusted based on the search histories from other users.

13. The computer-readable storage medium of claim 8 wherein the method further comprises:

caching the search results from a predicted search queries prior to selection of the search query by the user.

14. The computer-readable storage medium of claim 8 wherein search queries from the user comprise orders placed by the user on the search-based system based on the results of the search queries.

15. A computing system comprising:

a storage device configured to store search queries histories from all users of the computing system;

a processing device coupled to the storage device, the processing device comprising a search engine and a prediction engine,

wherein the search engine is configured to receive and track search queries from a user,

wherein the prediction engine is configured to compare a search query history from the user with search query histories from other users on the search engine and to generate a prediction of a search query for the user based on the comparison, search query histories from other users having greater similarities with the search query history from the user have a greater computation weight than search query histories from other users with less similarities with the search query history from the user.

16. The computing system of claim 15 wherein the prediction engine is configured to determine the number of common search queries between the search history of the user and the search history of each other user, to associate the search query history of the user with the search query of at least one other user having the most number of common search queries, to determine where a test sequence of the search history of the user is most similar to a reference sequence from at least one other user having the most number of common search queries, and to determine a new search query for the user from the search query history of at least one other user having the most number of common search queries based on the test sequence and the reference sequence.

17. The computing system of claim 15 wherein the prediction engine is configured to determine the number of common search queries between the search history of the user and the search history of other users, to associate the search query history of the user with the search query of at least another user having a minimum threshold of search queries similarities, to determine where a test sequence of the search history of the user is most similar to a reference sequence from at least another user having the minimum threshold of search queries similarities, and to determine a new search query for the user from the search query history of at least another user having the minimum threshold of search queries similarities based on the test sequence and the reference sequence.

18. The computing system of claim 15 wherein the computation weight is adjusted based on the search histories from other users.

19. The computing system of claim 15 wherein the prediction engine is further configured to cache the search results from a predicted search queries prior to selection of the search query by the user.

20. The computing system of claim 15 wherein search queries from the user comprise orders placed by the user on the search-based system based on the results of the search queries.