Refining A Search Space In Response To User Input

• US 20090094232A1
• Filed: 10/01/2008
• Published: 04/09/2009
• Est. Priority Date: 10/05/2007
• Status: Active Grant

• Current Assignee: Fujitsu Limited
• Original Assignee: Fujitsu Limited
• Inventors: Marvit, David L., Stergiou, Stergios, Jain, Jawahar
• Granted Patent: US 8,108,405 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3338 Query expansion
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence

Abstract

In one embodiment, a search space of a corpus is searched to yield results. The corpus comprises documents associated with keywords, where each document is associated with at least one keyword indicating at least one theme of the document. One or more keywords are determined to be irrelevant keywords. The search space is refined according to the irrelevant keywords.

Claims

1. A method comprising:

searching a search space of a corpus to yield a plurality of results, the corpus comprising a plurality of documents associated with a plurality of keywords, each document associated with at least one keyword indicating at least one theme of the document;

determining that one or more keywords are irrelevant keywords; and

refining the search according to the irrelevant keywords.

2. The method of claim 1, further comprising:

expanding the irrelevant keywords to include one or more other keywords related to the irrelevant keywords.

3. The method of claim 1, further comprising expanding the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by:

determining one or more irrelevant themes indicated by the irrelevant keywords;

identifying one or more affine themes that are highly affine to the irrelevant themes;

determining one of more affine keywords that correspond to the affine themes; and

identifying the affine keywords as the keywords related to the irrelevant keywords.

4. The method of claim 1, further comprising expanding the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by:

selecting one or more keywords that belong to the same cluster as the irrelevant keywords; and

identifying the selected keywords as the keywords related to the irrelevant keywords.

5. The method of claim 1, further comprising expanding the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by:

determining one or more irrelevant themes indicated by the irrelevant keywords;

identifying an implying theme that implies an irrelevant theme;

determining an implying keyword associated with the an implying theme; and

identifying the implying keyword as a keyword related to the irrelevant keywords.

6. The method of claim 1, further comprising expanding the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by:

receiving a user selection indicating how loosely or tightly related a keyword should be in order to be identified as a keyword related to an irrelevant keyword; and

identifying the keywords related to the irrelevant keywords according to the user selection.

7. The method of claim 1, further comprising presenting the results and the keywords associated with the results as one of the following:

a list of the results and the keywords;

an affinity graph of the keywords;

the results, each with a pop-up window of keywords;

or

the result, each with an expanding field of keywords.

8. The method of claim 1, the refining the search according to the irrelevant keywords further comprising:

removing the irrelevant keywords from the search query.

9. The method of claim 1, the refining the search according to the irrelevant keywords further comprising:

removing results associated with the irrelevant keywords.

10. The method of claim 1:

the corpus comprising the World Wide Web; and

the plurality of documents comprising a plurality of web pages.

11. The method of claim 1, the results comprising a plurality of feeds from a Web feed.

12. The method of claim 1, further comprising:

using a Boolean value to represent a relationship between two themes.

13. The method of claim 1, further comprising:

using a fuzzy logic to represent an ambiguous relationship between two themes.

15. The computer-readable of claim 11, the software further operable to:

expand the irrelevant keywords to include one or more other keywords related to the irrelevant keywords.

16. The computer-readable of claim 11, the software further operable to expand the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by:

determining one or more irrelevant themes indicated by the irrelevant keywords;

identifying one or more affine themes that are highly affine to the irrelevant themes;

determining one of more affine keywords that correspond to the affine themes; and

identifying the affine keywords as the keywords related to the irrelevant keywords.

17. The computer-readable of claim 11, the software further operable to expand the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by:

selecting one or more keywords that belong to the same cluster as the irrelevant keywords; and

identifying the selected keywords as the keywords related to the irrelevant keywords.

18. The computer-readable of claim 11, the software further operable to expand the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by:

determining one or more irrelevant themes indicated by the irrelevant keywords;

identifying an implying theme that implies an irrelevant theme;

determining an implying keyword associated with the an implying theme; and

identifying the implying keyword as a keyword related to the irrelevant keywords.

19. The computer-readable of claim 11, the software further operable to expand the irrelevant keywords to include one or more other keywords related to the irrelevant keywords by:

receiving a user selection indicating how loosely or tightly related a keyword should be in order to be identified as a keyword related to an irrelevant keyword; and

identifying the keywords related to the irrelevant keywords according to the user selection.

20. The computer-readable of claim 11, the software further operable to present the results and the keywords associated with the results as one of the following:

a list of the results and the keywords;

an affinity graph of the keywords;

the results, each with a pop-up window of keywords;

or

the result, each with an expanding field of keywords.

21. The method of claim 1, the software further operable to refine the search according to the irrelevant keywords by:

removing the irrelevant keywords from the search query.

22. The method of claim 1, the software further operable to refine the search according to the irrelevant keywords by:

removing results associated with the irrelevant keywords.

23. The computer-readable of claim 11:

the corpus comprising the World Wide Web; and

the plurality of documents comprising a plurality of web pages.

24. The computer-readable of claim 11, the results comprising a plurality of feeds from a Web feed.

25. The computer-readable of claim 11, the software operable to:

use a Boolean value to represent a relationship between two themes.

26. The computer-readable of claim 11, the software operable to:

use a fuzzy logic to represent an ambiguous relationship between two themes.

14. One or more tangible computer-readable media encoding software operable when executed to:

search a search space of a corpus to yield a plurality of results, the corpus comprising a plurality of documents associated with a plurality of keywords, each document associated with at least one keyword indicating at least one theme of the document;

determine that one or more keywords are irrelevant keywords; and

refine the search space according to the irrelevant keywords.