RELEVANCE OF NAME AND OTHER SEARCH QUERIES WITH SOCIAL NETWORK FEATURE

• US 20130110827A1
• Filed: 10/26/2011
• Published: 05/02/2013
• Est. Priority Date: 10/26/2011
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: SHENOY, RAJESH KRISHNA, NABAR, SHUBHA
• Application Number:
  US13/282,025
• Publication Number:
  US 20130110827A1
• Time in Patent Office: Days
• US Class Current: 707/728
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 10/00 Administration; Management

Abstract

Systems, computer-readable media, and methods for utilizing information pertaining to one or more individuals or entities with which a user has at least one social networking relationship are provided. A search engine is configured to receive a query, to identify matching electronic documents, to rank the electronic documents, and to transmit the matching electronic documents and/or advertisements to the user in response to receiving a query. Upon receiving the query from a user, the search engine obtains a social network identifier of the user and utilizes information about the user'"'"'s social networking relationships to augment the query with nonretrieval modifiers. The search engine processes the nonretrieval modifiers matching the electronic documents included in search results and ranks the results but does not use the nonretrieval modifiers to identify or retrieve results matching the query. The ranked electronic documents are included in the results and displayed in rank order to the user.

Claims

1. A computer-implemented method to rank electronic documents provided in a search engine result page, the method comprising:

receiving, by one or more computing devices, a query from a user;

determining, by the one or more computing devices, whether a social network identifier is available for the user;

when the social network identifier is available, performing, by the one or more computing devices, the following;

obtaining a social network graph of the user,

augmenting the query with weighted nonretrieval modifiers based on profile data obtained from the social network graph,

ranking electronic documents that match the query based on the search terms included in the query and the nonretrieval modifiers, and

transmitting the ranked documents to the user for display on a computing device; and

when the social network identifier is unavailable, performing, by the one or more computing devices, the following;

identifying electronic documents that match the query based on the search terms included in the query,

ranking electronic documents that match the query based on the search terms included in the query, and

transmitting the ranked documents to the user for display on a computing device.

2. The computer-implemented method of claim 1, further comprising:

classifying the query.

3. The computer-implemented method of claim 2, further comprising:

assigning weights to the weighted nonretrieval modifiers based on a classification associated with the query.

4. The computer-implemented method of claim 3, wherein the weights assigned to the weighted nonretrieval modifiers vary based on the classification of the query.

5. The computer-implemented method of claim 4, wherein the classification of the query is one or more of:

person, business, politics, sports, finance, movies, food, entertainment, directions, or general.

6. The computer-implemented method of claim 1, wherein the profile data includes items that the user likes.

7. The computer-implemented method of claim 1, wherein the profile data includes any of the following:

location, name, relationship status, hometown, education, and employment.

8. The computer-implemented method of claim 1, wherein ranking the electronic documents that match the query based on the search terms included in the query and the nonretrieval modifiers further comprises:

generating a score that is a sum of each of the weighted nonretrieval modifiers corresponding to matching profile data.

9. One or more memories having computer-executable instructions embodied thereon for performing a method to rank electronic index entries, the method comprising:

receiving, by one or more computing devices, a query from a user;

determining, by the one or more computing devices, whether a social network identifier is available for the user;

when the social network identifier is available, performing, by the one or more computing devices, the following;

obtaining a social network graph of the user,

augmenting the query with weighted nonretrieval modifiers based on profile data obtained from the social network graph,

ranking electronic index entries that correspond to documents that match the query based on the search terms included in the query and the nonretrieval modifiers, and

transmitting the ranked electronic entries to the user for display on a computing device; and

when the social network identifier is unavailable, performing, by the one or more computing devices, the following;

accessing an index tagged with social network identifiers for a plurality of entities,

determining whether the query matches any of the electronic entries included in the index,

clustering matching electronic entries based on the social network identifiers,

transmitting the results and the clustered electronic entries to the user for display on the computing device.

10. The memories of claim 9, further comprising:

classifying the query.

11. The memories of claim 10, further comprising:

assigning weights to the weighted nonretrieval modifiers based on a classification associated with the query.

12. The memories of claim 11, wherein the weights assigned to the weighted nonretrieval modifiers vary based on the classification of the query.

13. The memories of claim 12, wherein the classification of the query is one or more of:

person, business, sport, finance, movie, food, entertainment, directions, or general.

14. The memories of claim 9, wherein the profile data includes items that the user likes.

15. The memories of claim 9, wherein the profile data includes any of the following:

location, name, relationship status, hometown, education, and employment.

16. The memories of claim 9, wherein ranking the electronic entries that match the query based on the search terms included in the query and the nonretrieval modifiers further comprises:

generating a score that is a sum for each of the weighted nonretrieval modifiers corresponding to profile data matching content of the electronic entries.

17. A computer system that executes a search engine configured to rank electronic index entries, the system comprising:

an index of electronic entries for multimedia data; and

one or more processors configured to receive a query from a user, to determine whether a social network identifier is available for the user, when the social network identifier is available, to obtain a social network graph for the user, to augment the query with weighted nonretrieval modifiers based on profile data obtained from the social network graph, to rank electronic index entries that match the query based on the search terms included in the query and the nonretrieval modifiers, and to transmit the ranked index entries to the user for display on a computing device.

18. The system of claim 17, wherein the one or more processors are configured to tag the index with social network identifiers for a plurality of entities, to access the index tagged with social network identifiers for the plurality of entities, to determine whether the query matches any of the electronic entries included in the tagged index, to cluster matching electronic entries based on the social network identifiers, and to transmit the results and the clustered electronic entities to the user for display on the computing device.

19. The system of claim 17, wherein the one or more processors are configured to classify the query.

20. The system of claim 19, wherein the one or more processors are configured to assign weights to the weighted nonretrieval modifiers based on a classification associated with the query.