Method and apparatus for assigning a confidence level to a term within a user knowledge profile

• US 20020165861A1
• Filed: 04/01/2002
• Published: 11/07/2002
• Est. Priority Date: 09/18/1998
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Tacit Software, Inc. (Oracle Corporation)
• Inventors: Gilmour, David L.
• Granted Patent: US 6,832,224 B2
• Time in Patent Office: Days
• US Class Current: 707/7
• CPC Class Codes: G06F 16/313 Selection or weighting of terms for indexing
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing
• CPC Class Codes: Y10S 707/99953 Recoverability

Abstract

A method of assigning a confidence level to a term within an electronic document, such as an e-mail, includes the step of firstly determining a quantitative indicator in the exemplary form of an occurrence value, based on the number of occurrences of a particular term within an electronic document, and associating the occurrence term within the relevant term. Thereafter, a qualitative indicator, based on a quality of the term, is determined. For example, the qualitative indicator may be determined utilizing the parts of speech of words comprising the term. A confidence level value, which may be utilized to indicate a relative importance of the term in describing a user knowledge base, is then generated utilizing the quantitative and qualitative indicators.

Claims

1. A method of assigning a confidence level to a term within an electronic document, the method including the steps of:

determining a first quantitative indicator based on a number of occurrences of the term within the electronic document;

determining a characteristic indicator based on a characteristic of the term; and

assigning a second indicator to the term, the second indicator being derived from the first quantitative indicator and the characteristic indicator.

2. The method of claim 1 wherein the step of determining the first quantitative indicator includes the step of determining a number of occurrences of the term within the electronic document.

3. The method of claim 1 wherein the step of determining the first quantitative indicator includes the step of determining a frequency of occurrence of the term within the electronic document.

4. The method of claim 1 wherein the step of determining the first quantitative indicator includes the step of determining a density of occurrence of the term within the electronic document.

5. The method of claim 1 wherein the step of determining the characteristic indicator includes the step of determining the number of words comprising the term.

6. The method of claim 1 wherein the step of determining the characteristic indicator includes the step of determining parts of speech included within the term.

7. The method of claim 1 wherein the step of determining the characteristic indicator includes the step of determining whether a word within the term corresponds to a lexicon term.

8. The method of claim 1 including the step of summing second indicators, assigned to the term based on occurrences of the term within a plurality of electronic documents, to generate a summed indicator.

9. The method of claim 8 including the step of assigning a confidence level indicator to the term based on the summed indicator and the characteristic indicator.

10. The method of claim 9 including the step of scaling the confidence level indicator.

11. The method of claim 1 including the step of determining a third indicator based on addressee information associated with the electronic document.

12. The method of claim 11 wherein the step of determining the third indicator includes the identification of a level of seniority within an organization of an addressee of the electronic document.

13. The method of claim 11 wherein the step of determining the third indicator includes determining an average level of seniority within an organization of all addressees of the electronic document.

14. The method of claim 11 wherein the step of determining the third indicator includes determining a level of seniority within an organization of a most senior addressee of the electronic document.

15. The method of claim 12 including the step of generating a document weight term utilizing the level of seniority of the addressee of the electronic document.

16. The method of claim 11 wherein the step of determining the third indicator includes identification of a number of addressees of the electronic document.

17. The method of claim 16 including the step of generating a document weight term utilizing the number of addressees of the electronic document.

18. The method of claim 11 wherein the step of determining the third indicator includes identification of an organizational group of at least one addressee of the electronic document.

19. The method of claim 18 including the step of generating a document weight term utilizing the organizational group of the at least one addressee of the electronic document.

20. Apparatus for assigning a confidence level to a term within an electronic document, the apparatus comprising:

a term extractor to extract the term from the electronic document; and

confidence logic to determine a first quantitative indicator based on a number of occurrences of the term within the electronic document;

to determine a qualitative indicator based on a quality of the term; and

assign a second indicator, derived from the first quantitative indicator and the qualitative indicator, to the term.

21. The apparatus of claim 20 wherein the confidence logic determines a number of occurrences of the term within the electronic document.

22. The apparatus of claim 20 wherein the confidence logic determines a frequency of occurrence of the term within the electronic document.

23. The apparatus of claim 20 wherein the confidence logic determines a density of occurrence of the term within the electronic document.

24. The apparatus of claim 20 wherein the confidence logic determines the number of words comprising the term.

25. The apparatus of claim 20 wherein the confidence logic determines parts of speech included within the term.

26. The apparatus of claim 20 wherein the confidence logic determines whether a word within the term corresponds to a lexicon term.

27. The apparatus of claim 20 wherein the confidence logic sums second indicators, assigned to the term based on occurrences of the term within a plurality of electronic documents, to generate a summed indicator.

28. The apparatus of claim 27 wherein the confidence logic assigns a confidence level indicator to the term based on the summed quantitative indicator and the qualitative indicator.

29. The apparatus of claim 28 wherein the confidence logic scales the confidence level indicator.

30. The apparatus of claim 20 wherein the confidence logic determines a third indicator utilizing addressee information associated with the electronic document.

31. The apparatus of claim 30 wherein the confidence logic identifies a level of seniority within an organization of an addressee of the electronic document.

32. The apparatus of claim 30 wherein the confidence logic determines an average level of seniority within an organization of all addressees of the electric document.

33. The apparatus of claim 30 wherein the confidence logic determines a level of seniority within an organization of a most senior addressee of the electronic document.

34. The apparatus of claim 30 wherein the confidence logic determines a level of seniority within an organization of a most senior addressee of the electronic document.

35. The apparatus of claim 30 wherein the confidence logic identifies an organizational group of at least one addressee of the electronic document.

36. Apparatus for assigning a confidence level to a term within an electronic document, the apparatus comprising:

term extraction means for extracting a term from the electronic document; and

confidence means for determining a first quantitative indicator based on the number of occurrences of the term within the electronic document;

for determining a characteristic indicator based on a characteristic of the term;

and for assigning a second indicator, derived from the first quantitative indicator and the characteristic indicator, to the term.

37. A machine-readable medium storing a sequence of instructions that, when executed by a machine, cause the machine to perform the steps of:

determining a first quantitative indicator based on a number of occurrences of a term within an electronic document;

determining a qualitative indicator based on a quality of the term; and

assigning a composite indicator to the term, the composite indicator being derived from the first quantitative indicator and the qualitative indicator.