Weighted preference data search system and method

• US 6,714,929 B1
• Filed: 04/13/2001
• Issued: 03/30/2004
• Est. Priority Date: 04/13/2001
• Status: Expired due to Term

• Current Assignee: Viteds LLC
• Original Assignee: Auguri Corporation (Element Data, Inc.)
• Inventors: Sawey, Richard, Micaelian, Fadi Victor, Criswell, David Brandon, Scoffone, Emil Mario
• Primary Examiner(s): AMSBURY, WAYNE P
• Application Number:
  US09/834,441
• Time in Patent Office: 1,082 Days
• Field of Search: 707/4
• US Class Current: 1/1
• 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 method for weighted preference data searching comprising:

determining weighted preference information including a plurality of search criteria and a corresponding plurality of weights signifying the relative importance of said search criteria and allowing tradeoffs expressed as a plurality of normalized fixed sum weights wherein determining weighted preference information includes;

a) determining whether there should be user input;

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

c) determining whether the user should be able to select criteria;

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

e) inputting user selection of criteria if the user is allowed to select criteria;

f) determining whether the user should be able to adjust weights;

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

h) inputting user selected weights if the user is allowed to adjust weights;

i) determining whether the user should be able to input subjective ordering;

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

k) inputting user subjective ordering if the user is allowed to subjectively order; and

querying a data source and ranking the results based upon said weighted preference information.

2. A computer-implemented method for weighted preference data searching comprising:

determining weighted preference information including a plurality of search criteria and a corresponding plurality of weights signifying the relative importance of said search criteria wherein determining weighted preference information includes;

a) determining whether there should be user input;

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

c) determining whether the user should be able to select criteria;

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

e) inputting user selection of criteria if the user is allowed to select criteria;

f) determining whether the user should be able to adjust weights;

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

h) inputting user selected weights if the user is allowed to adjust weights;

i) determining whether the user should be able to input subjective ordering;

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

k) inputting user subjective ordering if the user is allowed to subjectively order; and

querying a data source and ranking the results based upon said weighted preference information.

3. A computer-implemented method for weighted preference data searching as recited in claim 2 wherein said data source is a database.

4. A computer-implemented method for weighted preference data searching as recited in claim 3 wherein said database is a relational database.

5. A computer-implemented method for weighted preference data searching as recited in claim 2 wherein said data source is a data stream.

6. A computer-implemented method for weighted preference data searching as recited in claim 5 wherein said data stream is buffered in a computer readable media.

7. A computer-implemented method for weighted preference data searching as recited in claim 2 further comprising determining a subjective ordering for at least one of said search criteria.