Weighted preference data search system and method

• US 7,194,458 B1
• Filed: 02/13/2004
• Issued: 03/20/2007
• Est. Priority Date: 04/13/2001
• Status: Expired due to Term

• Current Assignee: Viteds LLC
• Original Assignee: Auguri Corporation (Element Data, Inc.)
• Inventors: Micaelian, Fadi Victor, Criswell, David Brandon, Scoffone, Emil Mario, Sawey, Richard
• Primary Examiner(s): LEROUX, ETIENNE PIERRE
• Application Number:
  US10/778,907
• Time in Patent Office: 1,131 Days
• Field of Search: 707/1, 707/2, 707/9, 707/10, 707/3, 705/26, 709/224
• US Class Current: 707/706
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: Y10S 707/954 Relational
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation

Abstract

A search engine for databases, data streams, and other data sources allows user preferences as to the relative importance of search criteria to be used to rank the output of the search engine. A weighted preference generator generates weighted preference information including at least a plurality of weights corresponding to a plurality of search criteria. A weighted preference data search engines uses the weighted preference information to search a data source and to provide an ordered result list based upon the weighted preference information. A method for weighted preference data searching includes determining weighted preference information including a plurality of search criteria and a corresponding plurality of weights signifying the relative importance of the search criteria, and querying a data source and ranking the results based upon the weighted preference information. In addition to allowing client input of the relative importance of various search criteria, the system and method also preferably include the ability to provide a subjective ordering for at least some of the search criteria.

Claims

1. A computer-implemented weighted preference data search system comprising:

a weighted preference generator which generates a weighted preference query with tradeoffs expressed as a plurality of normalized fixed sum weights including at least a plurality of weights corresponding to a plurality of automobile related search criteria, the weighted preference generator including;

a means for determining whether there should be user input;

a means for providing at least one of default and automatic heuristically determined weighted preference information if there is not to be user input;

a means for determining whether the user should be able to select criteria;

a means for providing at least one of default and automatic heuristically determined criteria selections if the user is not able to select criteria;

a means for inputting user selection of criteria if the user is allowed to select criteria;

a means for determining whether the user should be able to adjust weights;

a means for providing at least one of default and automatic heuristically determined weights if the user is not able to adjust weights;

a means for inputting user selected weights if the user is allowed to adjust weights;

a means for determining whether the user should be able to input subjective ordering;

a means for providing at least one of default and automatic heuristically determined subjective ordering if the user is not able to subjectively order;

a means for inputting user subjective ordering if the user is allowed to subjectively order; and

a weighted preference data search engine which uses said weighted preference query to search a data source and to provide an ordered automobile result list based upon said weighted preference query.

2. A computer-implemented weighted preference data search system as recited in claim 1 wherein said data source is a database.

3. A computer-implemented weighted preference data search system as recited in claim 2 wherein said database is a relational database.

4. A computer-implemented weighted preference data search system as recited in claim 1 wherein said data source is a data stream.

5. A computer-implemented weighted preference data search system as recited in claim 4 wherein said data stream is buffered in a computer readable media.

6. A computer-implemented weighted preference data search system as recited in claim 1 wherein said weighted preference generator is a client to said weighted preference data search engine.

7. A computer-implemented weighted preference data search system as recited in claim 1 wherein said weighted preference generator is integrated with said weighted preference data search engine.

8. A computer-implemented weighted preference data search system as recited in claim 6 wherein said weighted preference generator further includes a user interface which allows user input of preferences.

9. A computer-implemented weighted preference data search system as recited in claim 8 wherein said preferences include at least one of the selection of search criteria, the adjustment of weights with respect to said search criteria, and an optional indication of subjective ordering for the search criteria wherein the optional indication of subjective ordering for the search criteria is set by a user of the computer-implemented weighted preference data search system.

10. A computer-implemented weighted preference data search system as recited in claim 7 wherein said weighted preference generator provides said weighted preference information based upon at least one of default values, automated heuristics, and user input.

11. A computer-implemented weighted preference data search system as recited in claim 1 wherein said weighted preference data search engine includes a data store and an algorithm processor.

12. A computer-implemented weighted preference data search system as recited in claim 11 wherein said weighted preference generator is a client of said weighted preference data search engine, and wherein said data store includes at least one of client preferences, historical search data, and intermediate search results.

13. A computer-implemented weighted preference data search system as recited in claim 11 wherein said algorithm processor includes a data source reader, a normalizing alternative distance calculator utilizing said weighted preference information and information from said data source reader, and an alternative scorer which creates a ranking for said alternatives based upon said normalized alternative distances and said weighted preference information.