Culturally relevant search results

• US 20080021860A1
• Filed: 10/04/2006
• Published: 01/24/2008
• Est. Priority Date: 07/21/2006
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: AOL LLC (Apollo Global Management, Inc.)
• Inventors: Vandermolen, Harmannus, Sommers, Michael, Howe, Karen, Wiegering, Anthony
• Granted Patent: US 7,624,103 B2
• Time in Patent Office: Days
• US Class Current: 707/1
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation

Abstract

Search results may be provided to a user. A search query may be received from the user. A query feature vector may be formed for the search query. The query feature vector may be compared with news feature vectors associated with documents related to current events. An augmented query feature vector may be formed based on results of the comparison of the query feature vector with the news feature vectors. The augmented query feature vector may be compared with feature vectors related to target documents. Search results that include target documents may be identified based on results of the comparison of the augmented query feature vector with the feature vectors related to the target documents. The user may be made able to perceive at least some of the identified search results.

Claims

1. A method for providing search results to a user, the method comprising:

receiving a search query from the user;

forming a query feature vector for the search query;

comparing the query feature vector with news feature vectors associated with documents related to current events;

forming an augmented query feature vector based on results of the comparison of the query feature vector with the news feature vectors;

comparing the augmented query feature vector with feature vectors related to target documents;

identifying search results that include target documents based on results of the comparison of the augmented query feature vector with the feature vectors related to the target documents; and

enabling the user to perceive at least some of the identified search results.

2. The method of claim 1 wherein enabling the user to perceive the identified search results comprises enabling the user to perceive only the identified search results.

3. The method of claim 2 further comprising:

determining relevance of each of the identified search results to the search query; and

sorting the identified search results based on the determined relevance.

4. The method of claim 1 wherein enabling the user to perceive the search results comprises:

sorting the identified search results into a first group of search results including identified search results that are closely related to a current event and a second group including identified search results that have no particular known relationship with the current event; and

enabling the user to perceive a difference between the first and second groups of identified search results.

5. The method of claim 1 further comprising enabling the user to perceive other search results in addition to and integrated with the identified search results.

6. The method of claim 5 further comprising:

determining relevance of each identified and other search result to the search query; and

sorting the identified and other search results based on the determined relevance.

7. The method of claim 1 wherein forming the augmented query feature vector comprises:

identifying terms that are included in the news feature vector, but absent from the query feature vector; and

forming the augmented query feature vector by adding the identified terms to the query feature vector.

8. The method of claim 1 wherein forming the augmented query feature vector comprises:

identifying terms included in the query feature vector, but absent from the news feature vector; and

forming the augmented query feature vector by removing the identified terms from the query feature vector.

9. The method of claim 1 wherein forming the augmented query feature vector comprises:

identifying terms included in the query feature vector that are similar to, but different from, terms included in the news feature vector; and

forming the augmented query feature vector by modifying the identified terms in the query feature vector to conform to the identified terms in the news feature vector.

10. The method of claim 1 further comprising:

comparing the query feature vector with the news feature vectors; and

determining news result feature vectors based on results of the comparison of the query feature vector with the news feature vectors,

wherein forming the augmented query feature vector comprises forming the augmented query feature vector based on the news result feature vectors.

11. The method of claim 10 wherein comparing the augmented query feature vector with the feature vectors related to target documents comprises comparing the augmented query feature vector with target feature vectors associated with target documents to identify the search results.

12. The method of claim 1 further comprising:

comparing the query feature vector with the news feature vectors;

determining news result feature vectors based on results of the comparison of the query feature vector with the news feature vectors; and

determining a centroid feature vector based on the news result feature vectors, wherein the centroid feature vector is determined based on at least one of clustering and determining a weighted average of the news feature vectors,

wherein forming the augmented query feature vector comprises forming the augmented query feature vector based on the centroid feature vector.

13. The method of claim 12 wherein comparing the augmented query feature vector with feature vectors related to target documents comprises comparing the augmented query feature vector with target feature vectors associated with target documents to identify the search results.

14. The method of claim 1 further comprising

comparing the query feature vector with the news feature vectors;

determining news result feature vectors based on results of the comparison of the query feature vector with the news feature vectors; and

determining a centroid feature vector based on the news result feature vectors, wherein the centroid feature vector is determined based on at least one of clustering and determining a weighted average of the news feature vectors,

wherein forming the augmented query feature vector comprises forming the augmented query feature vector based on the centroid feature vector.

15. The method of claim 14 wherein comparing the augmented query feature vector with the feature vectors related to target documents comprises comparing the augmented query feature vector with the temporary feature vectors to identify the search results.

16. The method of claim 1 further comprising:

accessing a target corpus data store that references target documents, wherein target documents include at least some documents related to current events; and

forming a target feature vector for each target document.

17. The method of claim 1 further comprising:

accessing a news corpus data store that references documents related to current events, wherein the current events are events related to human action; and

forming a news feature vector for each document related to the current events.

18. The method of claim 1 wherein enabling the user to perceive the search results comprises:

determining a relationship between the search results and a current event; and

providing the search results to the user as a perceivable list of search results organized with search results that are closely related to the current event being positioned closer to the top of the list than other search results.

19. The method of claim 1 wherein enabling the user to perceive the search results comprises:

distinguishing search results that are closely related to a current event from search results that have no particular known relationship with the current event; and

providing the search results to the user as a perceivable list of search results organized with the search results that are closely related to the current event being separated from the search results that have no particular known relationship with the current event using a label.

20. The method of claim 1 wherein enabling the user to perceive the search results comprises:

determining search results that are closely related to a current event;

determining search results that have no particular known relationship with the current event;

blending the search results that are closely related to the current event with the search results that have no particular known relationship with the current event; and

providing the search results to the user as a perceivable list of search results organized with the search results that are closely related to the current event being indistinguishable from the search results that have no particular known relationship with the current event.

21. The method of claim 1 wherein enabling the user to perceive the search results comprises:

determining search results that are closely related to a current event;

determining search results that have no particular known relationship with the current event;

blending the search results that are closely related to the current event with the search results that have no particular known relationship with the current event; and

providing the search results to the user as a perceivable list of search results organized with the search results that are closely related to the current event being distinguishable from the search results that have no particular known relationship with the current event.

22. A computer program product for providing search results to a user, the computer program product including instructions that, when executed, cause a processor to:

receive a search query from the user;

form a query feature vector for the search query;

compare the query feature vector with news feature vectors associated with documents related to current events;

form an augmented query feature vector based on results of the comparison of the query feature vector with the news feature vectors;

compare the augmented query feature vector with feature vectors related to target documents;

identify search results that include target documents based on results of the comparison of the augmented query feature vector with the feature vectors related to the target documents; and

enable the user to perceive at least some of the identified search results.

23. A system for providing search results to a user, the system comprising:

means for receiving a search query from the user;

means for forming a query feature vector for the search query;

means for comparing the query feature vector with news feature vectors associated with documents related to current events;

means for forming an augmented query feature vector based on results of the comparison of the query feature vector with the news feature vectors;

means for comparing the augmented query feature vector with feature vectors related to target documents;

means for identifying search results that include target documents based on results of the comparison of the augmented query feature vector with the feature vectors related to the target documents; and

means for enabling the user to perceive at least some of the identified search results.