Methods and systems for understanding a meaning of a knowledge item using information associated with the knowledge item

• US 20040243565A1
• Filed: 10/21/2003
• Published: 12/02/2004
• Est. Priority Date: 09/22/1999
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Weissman, Adam J., Elbaz, Gilad Israel
• Granted Patent: US 7,925,610 B2
• Time in Patent Office: Days
• US Class Current: 707/3
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G06F 16/3338 Query expansion
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06Q 30/0251 Targeted advertisements

Abstract

Systems and methods that determine a meaning of a knowledge item using related information are described. In one aspect, a knowledge item is received, related information associated with the knowledge item is received, at least one related meaning based on the related information is determined, and a knowledge item meaning for the knowledge item based at least in part on the related meaning is determined. Several algorithms and types of related information useful in carrying out such systems and methods are described.

Claims

1. A method, comprising:

receiving a knowledge item;

receiving related information associated with the knowledge item;

determining at least one related meaning based on the related information; and

determining a knowledge item meaning for the knowledge item based at least in part on the related meaning.

2. The method of claim 1, wherein the knowledge item is a keyword.

3. The method of claim 1, wherein the related information comprises related articles.

4. The method of claim 3, wherein the articles comprise an advertisement from an advertiser who has bid on the knowledge item.

5. The method of claim 4, wherein the articles further comprise a web page associated with the advertisement.

6. The method of claim 5, wherein the related information further comprises related data.

7. The method of claim 6, wherein the related data comprises cost per click data associated with the advertisement.

8. The method of claim 1, wherein receiving the knowledge item further comprises processing the knowledge item to determine any known associated concepts.

9. The method of claim 1, wherein the knowledge item comprises a plurality of associated concepts and determining the knowledge item meaning comprises determining which of the associated concepts represents the knowledge item meaning.

10. The method of claim 1, wherein the knowledge item comprises a plurality of concepts and the related meaning comprises a plurality of concepts and determining the knowledge item meaning comprises:

establishing a probability for each knowledge item concept that the knowledge item should be resolved to the knowledge item concept;

determining a strength of relationship between each knowledge item concept and each related meaning concept; and

adjusting the probability for each knowledge item concept based on the strengths.

11. The method of claim 1, wherein the knowledge item meaning comprises a weighted vector of concepts.

12. The method of claim 1, wherein the knowledge item meaning comprises related clusters of words.

13. The method of claim 1, wherein the knowledge item comprises a plurality of concepts, a plurality of related meanings are determined, each related meaning comprising a plurality of concepts, and determining the knowledge item meaning comprises:

establishing a probability for each knowledge item concept that the knowledge item should be resolved in part to the knowledge item concept; and

establishing a probability for each related meaning concept that the knowledge item should be resolved in part to the related meaning concept.

14. A computer-readable medium containing program code, comprising:

program code for receiving a knowledge item;

program code for receiving related information associated with the knowledge item;

program code for determining at least one related meaning based on the related information; and

program code for determining a knowledge item meaning for the knowledge item based at least in part on the related meaning.

15. The computer-readable medium of claim 14, wherein the knowledge item is a keyword.

16. The computer-readable medium of claim 14, wherein the related information comprises related articles.

17. The computer-readable medium of claim 16, wherein the articles comprise an advertisement from an advertiser who has bid on the knowledge item.

18. The computer-readable medium of claim 17, wherein the articles further comprise a web page associated with the advertisement.

19. The computer-readable medium of claim 18, wherein the related information further comprises related data.

20. The computer-readable medium of claim 19, wherein the related data comprises cost per click data associated with the advertisement.

21. The computer-readable medium of claim 14, wherein program code for receiving the knowledge item further comprises program code for processing the knowledge item to determine any known associated concepts.

22. The computer-readable medium of claim 14, wherein the knowledge item comprises a plurality of associated concepts and program code for determining the knowledge item meaning comprises program code for determining which of the associated concepts represents the knowledge item meaning.

23. The computer-readable medium of claim 14, wherein the knowledge item comprises a plurality of concepts and the related meaning comprises a plurality of concepts and determining the knowledge item meaning comprises:

program code for establishing a probability for each knowledge item concept that the knowledge item should be resolved to the knowledge item concept;

program code for determining a strength of relationship between each knowledge item concept and each related meaning concept; and

program code for adjusting the probability for each knowledge item concept based on the strengths.

24. The computer-readable medium of claim 14, wherein the knowledge item meaning comprises a weighted vector of concepts.

25. The computer-readable medium of claim 14, wherein the knowledge item meaning comprises related clusters of words.

26. The computer-readable medium of claim 14, wherein the knowledge item comprises a plurality of concepts, a plurality of related meanings are determined, each related meaning comprising a plurality of concepts, and determining the knowledge item meaning comprises:

program code for establishing a probability for each knowledge item concept that the knowledge item should be resolved in part to the knowledge item concept; and

program code for establishing a probability for each related meaning concept that the knowledge item should be resolved in part to the related meaning concept.