Method of and system for conducting personalized federated search and presentation of results therefrom

• US 8,577,915 B2
• Filed: 09/09/2011
• Issued: 11/05/2013
• Est. Priority Date: 09/10/2010
• Status: Active Grant

• Current Assignee: Veveo, Inc. (Adeia Inc.)
• Original Assignee: Veveo, Inc. (Adeia Inc.)
• Inventors: Barve, Rakesh, Garg, Pankaj, Venkataraman, Sashikumar, Aravamudan, Murali, Faldu, Keyur V., Agarwal, Vineet, Anand, Apurv
• Primary Examiner(s): Coby, Frantz
• Application Number:
  US13/229,229
• Publication Number:
  US 20120084277A1
• Time in Patent Office: 788 Days
• Field of Search: 707/700, 707/707, 707/758, 707/769, 709/201, 709/203, 709/213, 709/217
• US Class Current: 707/769
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

The present disclosure provides user-interface methods and systems for submitting search requests to search engines and presenting search results therefrom customized using content preferences learned about a user, comprising sending query information to at least two search engines, including a query identifying desired content, and user information, including context information describing the environment in which the query information is being sent, and a user signature representing content preferences learned about the user; receiving at least one set of a search result and auxiliary information from the at least one search engine in response to sending the query information, including information describing attributes of the search result that led to the search result being chosen by the at least one search engine; ordering the at least one search result based at least in part on the auxiliary information; and presenting the ordered search results to the user.

Claims

1. A computer-implemented user interface method of submitting search requests to at least two search engines and presenting search results therefrom customized using content preferences learned about a user, the method comprising:

sending query information to the at least two search engines, the query information including (a) a query identifying desired content, and (b) user information, the user information including (i) context information describing the environment in which the query information is being sent, the context information adapted into a syntax understandable by at least one of the at least two search engines, and (ii) a user signature representing content preferences learned about the user;

receiving at least one set of a search result and auxiliary information from the at least one of the at least two search engines in response to sending the query information, the auxiliary information of the set including information describing attributes of the search result of the set that led to the search result being chosen by the at least one of the at least two search engines;

ordering the at least one search result based at least in part on the auxiliary information; and

presenting the ordered search results to the user.

2. The method of claim 1, wherein the auxiliary information includes at least one of:

an identification of a dataspace associated with the corresponding search result,

an identification of a search engine that provided the search result,

a relevance list, wherein a relevance list element represents a set of an attribute of the search result and a value indicating the relevance of the attribute to at least one of the query and the user information,

a textual location list, wherein a textual location list element represents the location of search terms from the query information in fields provided by the search result,

a disjunction indicator list, wherein a disjunction indicator list element represents whether a corresponding search term from the query information matched the search result,

a spelling correction list, wherein a spelling correction list element represents whether a corresponding search term from the query information exactly matched a substring of fields from the search result, and wherein the spelling correction list element represents a value indicating the distance between the corresponding search term and the matched substring, if a match was based on an applied spelling correction,

a complete word match list, wherein a complete word match list element represents whether a corresponding search term from the query information exactly matched a full word of fields from the search result based on an applied spelling correction,

a field match list, wherein a field match list element represents whether the search query matched all words of a field of the search result,

a location proximity indicator representing a value for the distance from the search result to a specified location, and

a location query-place indicator representing whether a part of the search query matched an entity recognized to be a place having a location.

3. The method of claim 1, wherein the ordering is further based on search engine general information, the search engine general information describing the at least one search engine.

4. The method of claim 3, wherein the ordering based on the search engine general information is based on a comparison between the search engine general information and the user information.

5. The method of claim 4, wherein the search engine general information includes at least one of a measure of importance relative to other search engines of reordering criteria of different metacontent descriptor fields, a measure of importance relative to other search engines of spelling correction matches, a measure of importance relative to other search engines of disjunction indicators, relative interpretation of distance compared to other search engines for location indicators, whether the mere existence of a search result from the at least one search engine indicates that the search result should be presented as important, and the relative importance compared to other search engines of complete word matches.

6. The method of claim 1, further comprising selecting the search engines to which the query information is sent based on a measure of the use by the user of the corresponding search engines.

7. The method of claim 1, wherein the query identifying desired content includes at least one of a search query and a browse query, wherein the search query is initiated via at least one of text input by the user and text derived from alternative input by the user, the alternative input including at least one of speech, images, and barcode scans, and wherein the browse query is initiated via the user performing an action in a device application other than text input.

8. The method of claim 1, wherein the content preferences learned about the user include at least one of a user profile, user behavior, and user activity.

9. A system for submitting search requests to at least two search engines and presenting search results therefrom customized using content preferences learned about a user, the system comprising:

a computer memory store comprising instructions in computer readable form that when executed cause a computer system to

send query information to the at least two search engines, the query information including (a) a query identifying desired content, and (b) user information, the user information including (i) context information describing the environment in which the query information is being sent, the context information adapted into a syntax understandable by at least one of the at least two search engines, and (ii) a user signature representing content preferences learned about the user;

receive at least one set of a search result and auxiliary information from the at least one of the at least two search engines in response to sending the query information, the auxiliary information of the set including information describing attributes of the search result of the set that led to the search result being chosen by the at least one of the at least two search engines;

order the at least one search result based at least in part on the auxiliary information; and

present the ordered search results to the user.

10. The system of claim 9, wherein the auxiliary information includes at least one of:

an identification of a dataspace associated with the corresponding search result,

an identification of a search engine that provided the search result,

a relevance list, wherein a relevance list element represents a set of an attribute of the search result and a value indicating the relevance of the attribute to at least one of the query and the user information,

a textual location list, wherein a textual location list element represents the location of search terms from the query information in fields provided by the search result,

a disjunction indicator list, wherein a disjunction indicator list element represents whether a corresponding search term from the query information matched the search result,

a spelling correction list, wherein a spelling correction list element represents whether a corresponding search term from the query information exactly matched a substring of fields from the search result, and wherein the spelling correction list element represents a value indicating the distance between the corresponding search term and the matched substring, if a match was based on an applied spelling correction,

a complete word match list, wherein a complete word match list element represents whether a corresponding search term from the query information exactly matched a full word of fields from the search result based on an applied spelling correction,

a field match list, wherein a field match list element represents whether the search query matched all words of a field of the search result,

a location proximity indicator representing a value for the distance from the search result to a specified location, and

a location query-place indicator representing whether a part of the search query matched an entity recognized to be a place having a location.

11. The system of claim 9, wherein the ordering is further based on search engine general information, the search engine general information describing the at least one search engine.

12. The system of claim 11, wherein the ordering based on the search engine general information is based on a comparison between the search engine general information and the user information.

13. The system of claim 12, wherein the search engine general information includes at least one of a measure of importance relative to other search engines of reordering criteria of different metacontent descriptor fields, a measure of importance relative to other search engines of spelling correction matches, a measure of importance relative to other search engines of disjunction indicators, relative interpretation of distance compared to other search engines for location indicators, whether the mere existence of a search result from the at least one search engine indicates that the search result should be presented as important, and the relative importance compared to other search engines of complete word matches.

14. The system of claim 9, the computer memory store further comprising instructions that cause the computer system to select the search engines to which the query information is sent based on a measure of the use by the user of the corresponding search engines.

15. The system of claim 9, wherein the query identifying desired content includes at least one of a search query and a browse query, wherein the search query is initiated via at least one of text input by the user and text derived from alternative input by the user, the alternative input including at least one of speech, images, and barcode scans, and wherein the browse query is initiated via the user performing an action in a device application other than text input.

16. The system of claim 9, wherein the content preferences learned about the user include at least one of a user profile, user behavior, and user activity.