Method, system, and program for handling anchor text

• US 20050165781A1
• Filed: 01/26/2004
• Published: 07/28/2005
• Est. Priority Date: 01/26/2004
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kraft, Reiner, Neumann, Andreas
• Granted Patent: US 7,499,913 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 16/9558 Details of hyperlinks; Management of linked annotations
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

Disclosed is a method, system, and program for processing anchor text for information retrieval. A set of anchors that point to a target document is formed. Anchors with same anchor text are grouped together. Information is computed for each group. Context information is generated for the target document based on the computed information.

Claims

1. A method for processing anchor text, comprising:

forming a set of anchors that point to a target document;

grouping together anchors with same anchor text;

computing information for each group; and

generating context information for the target document based on the computed information.

2. The method of claim 1, further comprising:

determining a language of each document in a collection of documents;

determining rank of each document in the collection of documents; and

determining a proximity class of each document in the collection of documents.

3. The method of claim 1, further comprising:

determining a predominant language in the set of anchors; and

pruning anchors from the set that are not in the predominant language.

4. The method of claim 1, further comprising:

pruning anchors from the set that include at least a portion of a path to the target document.

5. The method of claim 1, further comprising:

pruning anchors based on a configurable set of words.

6. The method of claim 1, wherein computing information further comprises:

computing a weighted sum of occurrences for anchor text for anchors in each group.

7. The method of claim 1, wherein computing information further comprises:

computing an accumulated rank for each group.

8. The method of claim 1, wherein computing information further comprises:

computing a linguistic score for each group.

9. Them method of claim 1, wherein computing information further comprises:

generating a relevance score for each group.

10. A computer system including logic for processing anchor text, comprising:

forming a set of anchors that point to a target document;

grouping together anchors with same anchor text;

computing information for each group; and

generating context information for the target document based on the computed information.

11. The computer system of claim 10, wherein the logic further comprises:

determining a language of each document in a collection of documents;

determining rank of each document in the collection of documents; and

determining a proximity class of each document in the collection of documents.

12. The computer system of claim 10, wherein the logic further comprises:

determining a predominant language in the set of anchors; and

pruning anchors from the set that are not in the predominant language.

13. The computer system of claim 10, wherein the logic further comprises:

pruning anchors from the set that include at least a portion of a path to the target document.

14. The computer system of claim 10, wherein the logic further comprises:

pruning anchors based on a configurable set of words.

15. The computer system of claim 10, wherein the logic for computing information further comprises:

computing a weighted sum of occurrences for anchor text for anchors in each group.

16. The computer system of claim 10, wherein the logic for computing information further comprises:

computing an accumulated rank for each group.

17. The computer system of claim 10, wherein the logic for computing information further comprises:

computing a linguistic score for each group.

18. Them computer system of claim 10, wherein the logic for computing information further comprises:

generating a relevance score for each group.

19. An article of manufacture including a program for processing anchor text in documents, wherein the program causes operations to be performed, the operations comprising:

forming a set of anchors that point to a target document;

grouping together anchors with same anchor text;

computing information for each group; and

generating context information for the target document based on the computed information.

20. The article of manufacture of claim 19, wherein the operations further comprise:

determining a language of each document in a collection of documents;

determining rank of each document in the collection of documents; and

determining a proximity class of each document in the collection of documents.

21. The article of manufacture of claim 19, wherein the operations further comprise:

determining a predominant language in the set of anchors; and

pruning anchors from the set that are not in the predominant language.

22. The article of manufacture of claim 19, wherein the operations further comprise:

pruning anchors from the set that include at least a portion of a path to the target document.

23. The article of manufacture of claim 19, wherein the operations further comprise:

pruning anchors based on a configurable set of words.

24. The article of manufacture of claim 19, wherein the operations for computing information further comprise:

computing a weighted sum of occurrences for anchor text for anchors in each group.

25. The article of manufacture of claim 19, wherein the operations for computing information further comprise:

computing an accumulated rank for each group.

26. The article of manufacture of claim 19, wherein the operations for computing information further comprise:

computing a linguistic score for each group.

27. Them article of manufacture of claim 19, wherein the operations for computing information further comprise:

generating a relevance score for each group.