Intent match search engine

• US 20100017392A1
• Filed: 07/17/2009
• Published: 01/21/2010
• Est. Priority Date: 07/18/2008
• Status: Abandoned Application

• Current Assignee: Jianwei Dian
• Original Assignee: Jianwei Dian
• Inventors: Dian, Jianwei
• Application Number:
  US12/460,433
• Publication Number:
  US 20100017392A1
• Time in Patent Office: Days
• US Class Current: N/A
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence

Abstract

Method and apparatus for a query based search engine that searches a database of linked documents. In some embodiments, the method and apparatus computes reliability degrees of the documents, abstracts each document to generate its abstracts, provides a search query interface so that a user can use to enter a search query, processes the search query to generate an intent match criterion, identifies matched documents according to the generated intent match criterion, computes relevance degrees of the matched documents, sets order of the matched documents, and presents the matched documents to the user according to the set order by displaying the following items for each matched document: a link to the matched document, an abstract of the matched document if there are abstracts of the matched document, and a match in the matched document if there are matches in the matched document.

Claims

1. A method for a query based search engine that searches a database of linked documents, comprising:

(1.a) computing reliability degrees of the documents;

(1.b) abstracting each document to generate its abstracts;

(1.c) providing a search query interface so that a user can use to enter a search query;

(1.d) processing the search query to generate an intent match criterion;

(1.e) identifying matched documents according to the generated intent match criterion;

(1.f) computing relevance degrees of the matched documents;

(1.g) setting order of the matched documents; and

(1.h) presenting the matched documents to the user according to the set order by displaying the following items for each matched document;

a link to the matched document, an abstract of the matched document if there are abstracts of the matched document, and a match in the matched document if there are matches in the matched document.

2. The method of claim 1, wherein said abstracting each document to generate its abstracts comprises utilizing cross references among the documents to generate the abstracts.

3. The method of claim 1, wherein said processing the search query to generate an intent match criterion comprises performing syntax and semantics analysis to generate the intent match criterion.

4. The method of claim 1, wherein said identifying matched documents comprises taking a document as a matched document if there is a match in an abstract of the document or there is a match in the document itself.

5. The method of claim 4, further comprising, for each matched document:

(5.a) identifying all matches in each abstract of the matched document;

(5.b) computing separation degrees of all the matches in that particular abstract;

(5.c) taking a match in that particular abstract that has the least separation degree of the separation degrees of all the matches in that particular abstract as the match in that particular abstract, and taking the least separation degree of the separation degrees of all the matches in that particular abstract as the separation degree of the match in that particular abstract;

(5.d) identifying all matches in the matched document itself;

(5.e) computing separation degrees of all the matches in the matched document itself; and

(5.f) taking a match in the matched document itself that has the least separation degree of the separation degrees of all the matches in the matched document itself as the match in the matched document itself, and taking the least separation degree of the separation degrees of all the matches in the matched document itself as the separation degree of the match in the matched document itself.

6. The method of claim 5, wherein said computing relevance degrees of the matched documents comprises, for each matched document:

(6.a) computing relevance degrees of all matches in abstracts of the matched document and the match in the matched document itself; and

(6.b) taking the largest relevance degree of all the relevance degrees of all the matches in abstracts of the matched document and the match in the matched document itself as the relevance degree of the matched web page.

7. The method of claim 6, wherein said computing relevance degrees of all matches comprises, for each match:

(7.a) computing a location match degree of the match;

(7.b) computing an intent match degree of the match; and

(7.c) computing the relevance degree of the match based on the location match degree and the intent match degree.

8. The method of claim 7, wherein said computing an intent match degree of the match comprises computing the intent match degree based on separation degree of the match.

9. The method of claim 1, wherein said setting order of the matched documents comprises setting the order based on the relevance degrees and reliability degrees of the matched documents.

10. The method of claim 1, further comprising computing historical degrees of all documents that the user visited after the user completes a particular search with a particular search query.

11. The method of claim 10, wherein said setting order of the matched documents comprises setting the order based on the relevance degrees and reliability degrees of the matched documents, and, if any, historical degrees of the matched documents with respect to the user and with respect to the search query.

12. A query based search engine that searches a database of linked documents, comprising:

(12.a) first means for computing reliability degrees of the documents;

(12.b) second means for abstracting each document to generate its abstracts;

(12.c) a search query interface so that a user can use to enter a search query;

(12.d) third means for processing the search query to generate an intent match criterion;

(12.e) fourth means for identifying matched documents according to the generated intent match criterion;

(12.f) fifth means for computing relevance degrees of the matched documents;

(12.g) sixth means for setting order of the matched documents; and

(12.h) seventh means for presenting the matched documents to the user according to the set order by displaying the following items for each matched document;

a link to the matched document, an abstract of the matched document if there are abstracts of the matched document, and a match in the matched document if there are matches in the matched document.

13. The query based search engine of claim 12, wherein said second means comprises eighth means for utilizing cross references among the documents to generate the abstracts.

14. The query based search engine of claim 12, further comprising, for each matched document:

(14.a) ninth means for identifying all matches in each abstract of the matched document;

(14.b) tenth means for computing separation degrees of all the matches in that particular abstract;

(14.c) eleventh means for identifying the match in that particular abstract and the separation degree of the match in that particular abstract;

(14.d) twelfth means for identifying all matches in the matched document itself;

(14.e) thirteenth means for computing separation degrees of all the matches in the matched document itself; and

(14.f) fourteenth means for identifying the match in the matched document itself and the separation degree of the match in the matched document itself.

15. The query based search engine of claim 14, wherein said fifth means comprises, for each matched document:

(15.a) fifteenth means for computing relevance degrees of all matches in abstracts of the matched document and the match in the matched document itself; and

(15.b) sixteenth means for identifying the relevance degree of the matched web page.

16. The query based search engine of claim 12, wherein said sixth means comprises seventeenth means for setting the order based on the relevance degrees and reliability degrees of the matched documents.

17. The query based search engine of claim 12, further comprising eighteenth means for computing historical degrees of all documents that the user visited after the user completes a particular search with a particular search query.

18. The query based search engine of claim 17, wherein said sixth means comprises nineteenth means for setting the order based on the relevance degrees and reliability degrees of the matched documents, and, if any, historical degrees of the matched documents with respect to the user and with respect to the search query.

19. A method for abstracting a document in a database of linked documents to generate abstracts of the document comprising utilizing cross references among the documents to generate the abstracts.

20. A method for presenting a matched document to a user of a query based search engine that searches a database of linked documents comprising displaying the following items for the matched document:

a link to the matched document, an abstract of the matched document if there are abstracts of the matched document, and a match in the matched document if there are matches in the matched document.