Augmenting search with association information

• US 8,983,947 B2
• Filed: 09/30/2011
• Issued: 03/17/2015
• Est. Priority Date: 09/30/2011
• Status: Active Grant

• Current Assignee: Jive Software Incorporated (Wave Systems Corporation)
• Original Assignee: Jive Software Incorporated (Wave Systems Corporation)
• Inventors: Riedel, Lance, Mavromatis, Georgios
• Primary Examiner(s): CHANNAVAJJALA, SRIRAMA T
• Application Number:
  US13/250,326
• Publication Number:
  US 20130086071A1
• Time in Patent Office: 1,264 Days
• Field of Search: 707/708, 707/728, 707/731, 707/742, 707/754, 707/758, 707/766, 707/805, 715234-237, 715/751, 715762-763, 715/969
• US Class Current: 707/728
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06F 16/3338 Query expansion
• CPC Class Codes: G06F 3/048 Interaction techniques based on graphical user interfaces [GUI]
• CPC Class Codes: Y10S 715/968 interface for database querying and retrieval

Abstract

Techniques and tools are described for augmenting search using association information. Searches can be performed using a combination of index information and association information. In some examples, index information is stored in a first data store and association information is stored in a second data store. Search queries can be received and modified using association information. Modified search queries can be executed using a combination of index information and association information. Index information can be generated by indexing a set of documents. Association information can be generated by monitoring user activity occurring between users and a set of documents.

Claims

1. A method, implemented at least in part by a computing device, for performing a search using association information, the method comprising:

receiving a search query from a user;

generating a modified search query from the search query, wherein the modified search query is generated, at least in part, based upon association information between users and documents;

executing, by the computing device, the modified search query, wherein the executing the modified search query comprises;

identifying, based on association information, a set of documents listed in a second data store, wherein the second data store stores the association information which comprises relationships between the users and the documents for one or more social activity features;

receiving, from the user, a selection of at least one social activity feature, wherein the modified search query uses the association information for the at least one social activity feature; and

searching, using the search query, within the set of documents using a first data store, wherein the first data store comprises index information for the set of documents using, at least in part, an inverted index; and

returning, to the user, results of the execution of the modified search query;

wherein the identified set of documents listed in the second data store is a subset of all documents indexed within the first data store;

wherein the modified search query searches within the subset of all documents indexed within the first data store; and

wherein the subset of all documents indexed within the first data store is determined based on the association information from the second data store.

2. The method of claim 1, wherein the search query comprises one or more search terms entered by the user.

3. The method of claim 1, wherein the one or more social activity features comprise one or more of:

a “

like”

feature that indicates which documents users have liked;

a “

viewed”

feature that indicates which documents users have viewed; and

a “

friends viewed”

feature that indicates which documents users'"'"' friends have viewed.

4. The method of claim 1, wherein the second data store stores the association information as dynamic entries in the second data store, and wherein the association information is stored in near-real-time as associations between the users and the documents occur.

5. The method of claim 1, wherein the first data store and the second data store operate within the same vector space.

6. A search system for performing searches using association information, the search system comprising:

a first data store that stores index information for documents using, at least in part, an inverted index; and

a second data store that stores association information between users and the documents, wherein the association information comprises relationships between the users and the documents for one or more social activity features;

wherein the search system is configured to;

receive search queries from the users;

generate modified search queries from the search queries, wherein the modified search queries are generated, at least in part, based upon the association information between the users and the documents; and

execute the modified search queries using a combination of information from the first data store and the second data store by, for each modified search query;

identifying, based on the association information, a set of documents listed in the second data store;

receiving, from a user, a selection of at least one social activity feature, wherein the modified search query uses the association information for the at least one social activity feature;

searching, using the search query, within the set of documents using the first data store; and

returning, to the user, results of the execution of the modified search query;

wherein the identified set of documents listed in the second data store is a subset of all documents indexed within the first data store;

wherein the search query searches within the subset of all documents indexed within the first data store; and

wherein the subset of all documents indexed within the first data store is determined based on the association information from the second data store.

7. The search system of claim 6, wherein second data store stores the association information as dynamic entries in the second data store, and wherein the association information is stored in near-real-time as associations between the users and the documents occur.

8. The search system of claim 6, wherein the one or more social activity features comprise one or more of:

a “

like”

feature that indicates which documents users have liked;

a “

viewed”

feature that indicates which documents users have viewed; and

a “

friends viewed”

feature that indicates which documents users'"'"' friends have viewed.

9. The search system of claim 6, wherein the association information stored by the second data store comprises:

for each user and for each social activity feature;

a list of documents, identified by document identifier, that have been associated with the user for the social activity feature.

10. The search system of claim 6, wherein the first data store stores mappings between terms and documents that contain those terms, and wherein the first data store is updated periodically.

11. The search system of claim 6, wherein the first data store and the second data store operate within the same vector space.

12. A computer-readable medium storing computer-executable instructions for causing a computing device to perform a method for performing a search using association information, the method comprising:

receiving a search query from a user, wherein the search query comprises one or more search terms;

generating a modified search query from the search query, wherein the modified search query is generated, at least in part, based upon association information between users and documents;

executing the modified search query, wherein the executing the modified search query comprises;

identifying, based on association information, a set of documents listed in a second data store, wherein the second data store stores the association information which comprises relationships between the users and the documents for one or more social activity features, wherein the second data store stores the association information as dynamic entries in the second data store, and wherein the association information is stored in near-real-time as associations between the users and the documents occur;

receiving, from the user, a selection of at least one social activity feature, wherein the modified search query uses the association information for the at least one social activity feature; and

searching, using the search query, within the set of documents using a first data store, wherein the first data store comprises index information for the set of documents using, at least in part, an inverted index; and

returning, to the user, results of the execution of the modified search query;

wherein the identified set of documents listed in the second data store is a subset of all documents indexed within the first data store;

wherein the modified search query searches within the subset of all documents indexed within the first data store; and

wherein the subset of all documents indexed within the first data store is determined based on the association information from the second data store.

13. The computer-readable medium of claim 12, wherein the one or more social activity features comprise one or more of:

a “

like”

feature that indicates which documents users have liked;

a “

viewed”

feature that indicates which documents users have viewed; and

a “

friends viewed”

feature that indicates which documents users'"'"' friends have viewed.

14. A method, implemented at least in part by a computing device, for generating data stores used for performing searches using association information, the method comprising:

indexing, at least in part by the computing device, a set of documents;

storing, in a first data store, index information from the indexing of the set of documents, wherein the index information is stored in the first data store using, at least in part, an inverted index;

monitoring, at least in part by the computing device, activity between users and the set of documents; and

storing, in a second data store, association information obtained from the monitoring of the activity, wherein the second data store stores the association information as dynamic entries in the second data store, wherein the association information does not consider content contained within the set of documents, wherein the monitoring of the activity and the storing the association information are performed in near-real-time as the activity between the users and the set of documents occur, and wherein the first data store and the second data store provide information for responding to expanded search queries, wherein;

the expanded search queries search a subset of the set of documents based on the index information; and

the subset of the set of documents is determined based on the association information from the second data store.

15. The method of claim 14, wherein the indexing the set of documents and the storing the index information occurs periodically, and wherein the monitoring of the activity and the storing the association information are performed more frequently than the indexing the set of documents and the storing the index information.

16. The method of claim 14, wherein the indexing the set of documents and the storing the index information occurs periodically, the method further comprising:

storing, in the second data store, dynamic information regarding the set of documents that has occurred since the storing the index information in the first data store.

17. The method of claim 14, wherein the first data store and the second data store operate within the same vector space, and wherein the first data store and the second data store perform internal to external document identifier (ID) translation.

18. The method of claim 14, wherein the first data store and the second data store provide information for responding to the expanded search queries using a combination of information from the first data store and the second data store.