Method & Apparatus for Identifying Contract Characteristics

• US 20100268528A1
• Filed: 04/16/2009
• Published: 10/21/2010
• Est. Priority Date: 04/16/2009
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Jamison, Robert Marc, Kamon, Ammiel, Raskina, Olga
• Application Number:
  US12/424,659
• Publication Number:
  US 20100268528A1
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 50/18 Legal services

Abstract

A contract characteristic identification application includes a user interface, a plurality of contract characteristic definitions, a natural language processing module and a characteristic identification function. At least one contract characteristic is defined and evaluated and the text of at least one contract is entering into the application. A document evaluation function included in the natural language processing module operates to evaluate the contents of the text of the contract against the defined contract characteristic and returns a listing of contract text that is closest to the defined contract characteristic of interest.

Claims

1. A method for identifying one or more document characteristics, comprising:

entering and storing the text of a document in a computer memory;

defining one or more document characteristics and storing them in the computer memory;

a trained natural language processing module operating on the one or more document characteristics to generate at least one value for each of the one or more document characteristics and operating on the text of the document to generate a plurality of document concept values; and

a document characteristic identification function employing the stored document characteristic values and the stored document concept values to identifying all document text that is within a preselected distance of the one or more defined document characteristics.

2. The method of claim 1 wherein each of the one or more document characteristics is associated with a defined degree of risk.

3. The method of claim 1 wherein the text of the document is one of a document clause, a document passage and document language of interest.

4. The method of claim 3 wherein the one of a document clause, a document passage and document language of interest is comprised of two or more words of textual information.

5. The method of claim 1 wherein each of the one or more document characteristics is associated with a different defined degree of risk.

6. The method claim 1 wherein the trained natural language processing module is comprised of a primary concept identification function and a secondary concept identification function.

7. The method of claim 1 wherein the document characteristic values represent a correlation between a characteristic identification element and a secondary document concept identified by the natural language processing module.

8. The method of claim 1 wherein the document concept value represents the correlation between document text and a secondary document concept identified by the natural language processing module.

9. A method for identifying a document characteristic, comprising:

entering the text of one or more documents into a document characteristic identification application;

defining one or more document characteristics and entering the one or more defined document characteristics into the document characteristic identification application;

the document characteristic identification application operating on the one or more entered document characteristics to generate a plurality of document characteristic values and operating on the entered text of the one or more documents to generate a plurality of document concept values; and

the document characteristic identification application employing the document characteristic values and the document concept values to identify all document text that is within a preselected distance of the one or more defined document characteristics.

10. The method of claim 9 wherein each of the one or more document characteristics is associated with a defined degree of risk.

11. The method of claim 9 wherein the text of the document is one of a document clause, a document passage and document language of interest.

12. The method of claim 11 wherein the one of a document clause, a document passage and document language of interest is comprised of two or more words of textual information.

13. The method of claim 9 wherein each of the one or more document characteristics is associated with a different defined degree of risk.

14. The method claim 9 wherein the document characteristic identification application is comprised of one or more document characteristic definitions, a natural language processing module and a characteristic identification function.

15. The method of claim 9 wherein the document characteristic values represent a correlation between a characteristic identification element and a secondary document concept identified by the document characteristic identification application.

16. The method of claim 9 wherein the document concept value represents the correlation between document text and a secondary document concept identified by the document characteristic identification application.

18. The computational device of claim 16 wherein each of the one or more document characteristics is associated with a defined degree of risk.

19. The computational device of claim 16 wherein the text of the document is one of a document clause, a document passage and document language of interest.

20. The computational device of claim 19 wherein the one of a document clause, a document passage and document language of interest is comprised of two or more words of textual information.

21. The computational device of claim 16 wherein each of the one or more document characteristics is associated with a different defined degree of risk.

22. The computational device of claim 16 wherein the document characteristic identification application is comprised of one or more document characteristic definitions, a natural language processing module and a characteristic identification function.

23. The computational device of claim 16 wherein the document characteristic values represent a correlation between a characteristic identification element and a secondary document concept identified by the document characteristic identification application.

24. The computational device of claim 16 wherein the document concept value represents the correlation between document text and a secondary document concept identified by the document characteristic identification application.

17. A computational device, comprising:

a user interface device;

a text entry device; and

a memory, the memory including;

a document characteristic identification application for operating on one or more of an entered document characteristics to generate a plurality of document characteristic values and operating on an entered text of a one or more documents to generate a plurality of document concept values; and

the document characteristic identification application employing the document characteristic values and the document concept values to identify all document text that is within a preselected distance of the one or more defined document characteristics