Content conversion method and apparatus

• US 20030061025A1
• Filed: 05/31/2002
• Published: 03/27/2003
• Est. Priority Date: 03/16/2001
• Status: Active Grant

• Current Assignee: Meaningful Machines LLC
• Original Assignee: Meaningful Machines LLC
• Inventors: Abir, Eli
• Granted Patent: US 8,744,835 B2
• Time in Patent Office: Days
• US Class Current: 704/7
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G06F 40/289 Phrasal analysis, e.g. finite state techniques or chunking
• CPC Class Codes: G06F 40/42 Data-driven translation
• CPC Class Codes: G06F 40/44 Statistical methods, e.g. probability models
• CPC Class Codes: G06F 40/45 Example-based machine translation; Alignment
• CPC Class Codes: G06F 40/47 Machine-assisted translation, e.g. using translation memory
• CPC Class Codes: G06F 40/55 Rule-based translation

Abstract

A method and apparatus for analyzing documents and thereby determining the association between words in a language. The method includes providing a collection of documents, selecting a first word or word string, and a second word or word string occurring in the documents. The method further involves associating first word or word strings and second word or word strings with common word or word strings based on frequency of occurrence of the common word or word strings within the ranges.

Claims

1. A method for associating words in a language comprising:

providing a collection of documents, wherein said collection includes at least one document;

selecting a first word or word string, and a second word or word string;

locating a plurality of occurrences of the first word or word string and the second word or word string in said collection;

defining in said collection first ranges and second ranges, wherein the first ranges include the first word or word string and the second ranges include the second word or word string;

searching said first ranges and second ranges for common word or word strings, wherein said common word or word strings occur in a plurality of ranges; and

associating first word or word strings and second word or word strings with common word or word strings based on frequency of occurrence of the common word or word strings within the first ranges and second ranges respectively.

2. The method of claim 1, wherein said associating first word or word strings and second word or word strings is enhanced by a greater frequency of occurrence of the common word or word strings.

3. The method of claim 1, wherein said associating first word or word strings and second word or word strings is enhanced by a lesser frequency of occurrence of the common word or word strings.

4. The method of claim 1, further comprising replacing the first word and/or word string with a substantially semantically equivalent word or word string.

5. A method for associating words in a language comprising:

providing a collection of documents, wherein said collection includes at least one document;

selecting a first word or word string, and a second word or word string;

locating all documents having a plurality of occurrences of the first word or word string within a defined proximity range of the second word and/or word string, with said defined proximity range having an upper limit and a lower limit;

defining in the located documents a range, wherein the range includes the first word or word string and the second word or word string;

searching said ranges for common word or word strings; and

associating the first word or word string and the second word or word string with common word or word strings based on frequency of occurrence of the common word or word strings within the ranges.

6. The method of claim 5, wherein said associating first word or word strings and second word or word strings is enhanced by a greater frequency of occurrence of the common word or word strings.

7. The method of claim 5, wherein said associating first word or word strings and second word or word strings is enhanced by a lesser frequency of occurrence of the common word or word strings.

8. The method of claim 5, wherein said upper and said lower limit of said defined proximity range are equal.

9. A method for creating an association database in a single language comprising the steps of:

providing a collection of documents, wherein said collection includes at least one document;

selecting a first word or word string;

locating a plurality of occurrences of the first word or word string;

defining in said collection ranges, wherein said ranges occur in relation to each of said plurality of occurrences of the first word or word string;

searching said ranges for common word or word strings, wherein said common word or word strings occur in a plurality of ranges; and

associating first word or word strings with common word or word strings based on frequency of occurrence of the common word or word strings within the ranges.