Ranking of objects using semantic and nonsemantic features in a system and method for conducting a search

• US 7,809,721 B2
• Filed: 11/16/2007
• Issued: 10/05/2010
• Est. Priority Date: 11/16/2007
• Status: Active Grant

• Current Assignee: IAC Search & Media Incorporated (Match Group, Inc.)
• Original Assignee: IAC Search & Media Incorporated (Match Group, Inc.)
• Inventors: Putivsky, Yuri, Kislyuk, Oleg S., Jouline, Anton V.
• Primary Examiner(s): Mofiz; Apu M
• Assistant Examiner(s): Le; Hung D
• Application Number:
  US11/941,696
• Publication Number:
  US 20090132468A1
• Time in Patent Office: 1,054 Days
• Field of Search: None
• US Class Current: 707/724
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

The invention provides for a system for ranking data including a first calculation component that calculates a qualitative semantic similarity score of at least one data entry from at least one data source, a second calculation component that calculates a general quantitative score of the at least one data entry from at least one data source, a third calculation component that combines the qualitative semantic similarity score and the general quantitative score of the at least one data entry from at least one data source into a vector score for the at least one data entry, and a ranking component that ranks the at least one data entry among other data entries using the vector score. General qualitative scores such as distance scores are never overruled by semantic scores.

Claims

1. A system for ranking data, comprising:

at least one processor;

at least one computer-readable storage medium connected to the processor;

a data store on the medium;

entries stored on the data store;

a series of instructions on the medium and executable by the processor, including;

a reception component that receives a query;

a first calculation component that calculates a qualitative semantic similarity score of a semantic part of the query by associating the semantic part with text from data entries in a data store;

a second calculation component that calculates a general quantitative score of by at least calculating a distance score for the data entries based on a geographic location part of the query;

a third calculation component that adds the general qualitative semantic similarity score and the general quantitative score to obtain a vector score for the at least one data entry, the general qualitative semantic similarity score and the quantitative score each having a range with a minimum value of the general qualitative score being more than a maximum value of the general quantitative semantic similarity score such that the general quantitative score is never overruled by the general qualitative similarity semantic score; and

a ranking component that ranks the at least one data entry among other data entries using the vector score.

2. The system of claim 1, wherein the quantitative semantic similarity score shows the qualitative relevancy of the particular location to the query.

3. The system of claim 1, wherein the general quantitative score comprises a semantic similarity score, a distance score, and a rating score.

4. A method for ranking data, comprising:

utilizing a computer processor to calculate a qualitative semantic similarity score of a semantic part of the query by associating the semantic part with text from data entries in a data store;

utilizing the computer processor to calculate a general quantitative score by at least calculating a distance score for the data entries based on a geographic location part of the query;

utilizing the computer processor to add the general qualitative similarity score and the general quantitative similarity score a vector score for the at least one data entry, the general qualitative semantic similarity score and the quantitative score each having a range with a minimum value of the general quantitative score being more than a maximum value of the general qualitative semantic similarity score such that the general quantitative score is never overruled by the general qualitative similarity semantic score; and

utilizing the computer processor to rank the at least one data entry among other data entries using the vector score.

5. The method of claim 4, wherein the quantitative semantic similarity score shows the qualitative relevancy of the particular location to the query.

6. The method of claim 5, wherein the general quantitative score comprises a semantic similarity score, a distance score, and a rating score.

7. A computer-readable medium, having stored thereon a set of instructions which, when executed by at least one processor of at least one computer, executes a method for ranking data comprising:

utilizing a computer processor to calculate a qualitative semantic similarity score of a semantic part of the query by associating the semantic part with text from data entries in a data store;

utilizing the computer processor to a general quantitative score by at least calculating a distance score for the data entries based on a geographic location part of the query;

utilizing the computer processor to add the general qualitative similarity score and the general quantitative similarity score a vector score for the at least one data entry, the general qualitative semantic similarity score and the quantitative score each having a range with a minimum value of the general quantitative score being more than a maximum value of the general qualitative semantic similarity score such that the general quantitative score is never overruled by the general qualitative similarity semantic score; and

utilizing the computer processor to rank the at least one data entry among other data entries using the vector score.