Data ranking with a Lorentzian fuzzy score

• US 7,257,586 B2
• Filed: 12/29/2003
• Issued: 08/14/2007
• Est. Priority Date: 09/12/2001
• Status: Expired due to Fees

• Current Assignee: Science Applications International Corporation
• Original Assignee: Science Applications International Corporation
• Inventors: Lau, Yun-Tung, Nagy, Marton
• Primary Examiner(s): LEROUX, ETIENNE PIERRE
• Application Number:
  US10/745,552
• Publication Number:
  US 20040139068A1
• Time in Patent Office: 1,324 Days
• Field of Search: 707/1, 707/2, 707/100, 707/7, 707/10, 707/9, 709/203
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2468 Fuzzy queries
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99936 Pattern matching access

Abstract

The present invention relates to a method for searching a document database such as the Internet and ranking the results obtained from such a search. The invention also relates to ranking of a set of numerical data according to a set of user specified preferences, including target range, fuzziness and bias. A fuzzy score is calculated for each database record satisfying a query and the results ranked according to fuzzy score. The fuzzy score is calculated using a Lorentzian fuzzy score formula.

Claims

1. A method for ranking a plurality of elements, wherein a numerical parameter characterizes each element, the method comprising:

ranking a plurality of elements based at least in part on a Lorenizian fuzzy score based at least in part on a numerical parameter characterizing each element.

2. The method of claim 1, further comprising, prior to ranking:

receiving an indication of at least one of fuzziness and bias as inputs to ranking.

3. The method of claim 2 wherein at least one indication is qualitative.

4. The method of claim 3 wherein each qualitative indication is mapped to a quantitative indication.

5. The method of claim 2 wherein at least one indication is quantitative.

6. A method for ranking a plurality of elements, wherein a plurality of numerical parameters characterizes each element, the method comprising:

ranking a plurality of elements based at least in part on an aggregate score;

the aggregate score based at least in part on a plurality of Lorentzian fuzzy scores;

each Lorentzian fuzzy score based at least in part on a numerical parameter characterizing each element.

7. The method of claim 6, further comprising, prior to ranking:

receiving an indication of at least one of fuzziness and bias as inputs to ranking.

8. The method of claim 7 wherein at least one indication is qualitative.

9. The method of claim 8 wherein each qualitative indication is mapped to a quantitative indication.

10. The method of claim 7 wherein at least one indication is quantitative.

11. The method of claim 6 wherein the aggregate score is basal at least in part on summing the Lorentzian fuzzy scores.

12. The method of claim 6 wherein the aggregate score is based at least in part on weighted summing of the Lorentzian fuzzy scores.

13. The method of claim 12 further comprising:

prior to ranking, receiving an indication of weight for at least one parameter.