Method and apparatus for searching network resources

• US 20050210018A1
• Filed: 04/29/2005
• Published: 09/22/2005
• Est. Priority Date: 08/18/2000
• Status: Active Grant

• Current Assignee: Aurea Software Incorporated (ESW Capital, LLC)
• Original Assignee: FirstRain, Inc. (Ignite Technologies Incorporated)
• Inventors: Singh, Jaswinder Pal, Wang, Randolph
• Granted Patent: US 7,415,469 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 40/131 Fragmentation of text files, e.g. creating reusable text-blocks; Linking to fragments, e.g. using XInclude; Namespaces
• CPC Class Codes: G06F 40/143 Markup, e.g. Standard Generalized Markup Language [SGML] or Document Type Definition [DTD]
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching

Abstract

The present invention pertains to the field of computer software. More specifically, the present invention relates to one more populating, indexing, and searching a database of fine-grained web objects or object specifications.

Claims

1. A method of searching electronic resources including markup language, comprising:

receiving a search query; and

at least partly responsive to the search query to search electronic resources, identifying at least one or more subportions of one or more documents, each of the one or more documents including markup language, each of the one or more subportions including markup language tags substantially preserved from the one or more documents, the search query used as a criterion for at least one of the one or more subportions.

2. The method of claim 1, further comprising:

ranking a list of the one or more subportions of the one or more documents, and basing ranking at least partly on relevance of one or more subportions to the search query.

3. The method of claim 2, wherein the relevance is at least partly based on content of the one or more subportions.

4. The method of claim 2, wherein the relevance is at least partly based on content of the one or more views.

5. The method of claim 1, further comprising:

returning a ranked list of the one or more subportions.

6. The method of claim 1, further comprising:

transcoding at least one of the one or more subportions at least partly into another format.

7. The method of claim 6, wherein the transcoding is at least partly based on a client type.

8. The method of claim 1, further comprising:

transcoding at least one of the one or more subportions at least partly into another media representation.

9. The method of claim 8, wherein the transcoding is at least partly based on a client type.

10. The method of claim 1, further comprising:

transcoding at least one of the one or more subportions at least partly into another markup language.

11. The method of claim 10, wherein the transcoding is at least partly based on a client type.

12. A method of searching resources including markup language, comprising:

generating a graph including

     1) one or more subportions of one or more documents, one or more documents including markup language,

     2) one or more references to one or more subportions of one or more documents and

     3) zero or more documents, the one or more references included in one or more documents, one or more documents including markup language; and

generating a ranked list of one or more subportions of one or more documents including markup language, such that ranking is based on relevance, to a search query, of one or more portions of one or more documents including markup language, the ranked list at least partly generated from the graph.

13. The method of claim 12, wherein the relevance is at least partly based on content of the one or more subportions.

14. The method of claim 12, wherein the relevance is at least partly based on content of the one or more views.

15. The method of claim 12, wherein the ranked list is generated by:

assigning weights to one or more subportions of one or more documents including markup language;

propagating weights through the graph; and

finding a consistent assignment of weights such that each weight assigned to a subset of a document equals a weighted sum weights propagated from neighboring subportions.

16. The method of claim 12, wherein the generated graph further includes one or more views, one or more views including one or more documents and one or more selections, one or more documents including markup language, one or more selections including one or more subportions of one or more documents.

17. The method of claim 16, wherein the views are content-sensitive filters that specify which sub-parts of a web page a user is interested in.

18. The method of claim 16, wherein the ranked list is generated by:

assigning weights to one or more views and one or more subportions of one or more documents including markup language;

propagating weights through the graph; and

finding a consistent assignment of weights such that each weight assigned to a subset of a document based at least partly on a weighted sum of weights propagated from neighboring subportions.

19. The method of claim 16, wherein the generated ranked list further includes one or more views, one or more views including one or more documents and one or more selections, one or more documents including markup language, one or more selections including one or more subportions of one or more documents.

20. A method searching resources including markup language, comprising:

generating a graph including

     1) one or more one or more subportions of one or more documents, one or more documents including markup language

     2) one or more references to one or more subportions of one or more documents, the one or more references included in a first of one or more documents, one or more documents including markup language,

     3) zero or more documents,

     4) one or more views, one or more views including one or more documents and one or more selections, one or more documents including markup language, one or more selections including one or more subportions of one or more documents; and

generating a ranked list of one or more views, such that ranking is based on relevance, to a search query, of one or more portions of one or more documents including markup language, the ranked list at least partly generated from the graph, one or more views including one or more documents and one or more selections, one or more documents including markup language, one or more selections including one or more subportions of one or more documents.

21. The method of claim 20, wherein the relevance is at least partly based on content of the one or more subportions.

22. The method of claim 20, wherein the relevance is at least partly based on content of the one or more views.

23. The method of claim 20, wherein the ranked list is generated by:

assigning weights to one or more views and one or more subportions of one or more documents including markup language;

propagating weights through the graph; and

finding a consistent assignment of weights such that each weight assigned to a subset of a document is based at least partly on a weighted sum of weights propagated from neighboring subportions.

24. The method of claim 20, wherein the views are content-sensitive filters that specify which sub-parts of a web page a user is interested in.

25. A computerized system for searching, the system comprising:

a view repository;

a database;

means for receiving a search query; and

means for, at least partly responsive to the search query to search electronic resources, identifying at least one or more subportions of one or more documents, each of the one or more documents including markup language, each of the one or more subportions including markup language tags substantially preserved from the one or more documents, the search query used as a criterion for at least one of the one or more subportions.

26. The system of claim 25, wherein the documents comprise web pages.