METHOD AND SYSTEM OF EXTRACTING CONCEPTS AND RELATIONSHIPS FROM TEXTS

• US 20130007020A1
• Filed: 06/30/2011
• Published: 01/03/2013
• Est. Priority Date: 06/30/2011
• Status: Abandoned Application

• Current Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Original Assignee: Hewlett Packard Enterprise Development LP (Hewlett-Packard Enterprise Company)
• Inventors: Basu, Sujoy, Singhal, Sharad
• Application Number:
  US13/173,643
• Publication Number:
  US 20130007020A1
• Time in Patent Office: Days
• US Class Current: 707/750
• CPC Class Codes: G06F 16/367 Ontology

Abstract

An exemplary embodiment of the present techniques extracts concepts and relationships from a text. Concepts may be generated from the text using singular value decomposition, and ranked based on a term weight and a distance metric. The concepts that are ranked above a particular threshold may be iteratively extracted, and the concepts may be merged to form larger concepts until the generation of concepts has stabilized. Relationships may be generated based on the concepts using singular value decomposition, then ranked based on various metrics. The relationships that are ranked above a particular threshold may be extracted.

Claims

1. A system for extracting concepts and relationships from a text, comprising:

a processor that is adapted to execute stored instructions; and

a memory device that stores instructions, the memory device comprising processor-executable code, that when executed by the processor, is adapted to;

generate concepts from the text using singular value decomposition;

rank the concepts based on a term weight and a distance metric;

extract the concepts iteratively that are ranked above a particular threshold;

merge the concepts to form larger concepts until concept generation has stabilized;

generate relationships based on the concepts using singular value decomposition;

rank the relationships based on various metrics; and

extract the relationships that are ranked above a particular threshold.

2. The system recited in claim 1, wherein the memory device comprises processor-executable code, that when executed by the processor, is adapted to generate concepts from the text using singular value decomposition by:

creating a matrix to generate concepts, said matrix having rows that represent unigrams or multi-grams and columns that represent documents; and

expressing the matrix as a product of three matrices, including a diagonal matrix of singular values ordered in descending order, a matrix representing terms, and a matrix representing documents, using singular value decomposition.

3. The system recited in claim 1, wherein the memory device comprises processor-executable code, that when executed by the processor, is adapted to generate relationships based on the concepts using singular value decomposition by:

creating a matrix to generate relationships, said matrix having rows that represent single words, concepts, and triples and columns that represent documents; and

expressing the matrix another as a product of three matrices using singular value decomposition.

4. The system recited in claim 1, wherein the various metrics include another term weight, another distance metric, a number of elementary words in the concepts connected by the relationship, or a TFIDF weight of the concepts.

5. The system recited in claim 1, wherein seed concepts are provided.

6. The system recited in claim 1, wherein the relationship is expressed by one or more verbs, or a verb and a preposition, or a noun and a preposition, or any other pattern known for relationships.

7. The system recited in claim 1, wherein a mind map of concepts and relationships is rendered.

8. A method of extracting concepts and relationships from a text, comprising:

generating concepts from the text using singular value decomposition;

ranking the concepts based on a term weight and a distance metric;

extracting the concepts iteratively that are ranked above a particular threshold;

merge the concepts to form larger concepts until concept generation has stabilized;

generating relationships based on the concepts using singular value decomposition;

ranking the relationships based on various metrics; and

extracting the relationships that are ranked above a particular threshold.

9. The method recited in claim 8, wherein generating concepts from the text using singular value decomposition comprises:

creating a matrix to generate concepts, said matrix having rows that represent unigrams or multi-grams and columns that represent documents; and

expressing the matrix as a product of three matrices, including a diagonal matrix of singular values ordered in descending order, a matrix representing terms, and a matrix representing documents, using singular value decomposition.

10. The method recited in claim 8, wherein generating relationships based on the concepts using singular value decomposition comprises:

creating a matrix to generate relationships, said matrix having rows that represent single words, concepts, and triples and columns that represent documents; and

expressing the matrix another as a product of three matrices using singular value decomposition.

11. The method recited in claim 8, wherein the various metrics include another term weight, another distance metric, a number of elementary words in the concepts connected by the relationship, or a TFIDF weight of the concepts.

12. The method recited in claim 8, wherein seed concepts are provided.

13. The method recited in claim 8, wherein the relationship is expressed by one or more verbs, or a verb and a preposition, or a noun and a preposition, or any other pattern known for relationships.

14. The method recited in claim 8, wherein a mind map of concepts and relationships is rendered.

15. A non-transitory, computer-readable medium, comprising code configured to direct a processor to:

pre-process documents using a pre-process module;

generate concepts from the pre-processed documents using singular value decomposition;

rank the concepts based on a term weight and a distance metric;

extract the concepts that are ranked above a particular threshold using an iterative concept generation module;

merge the concepts to form larger concepts until concept generation has stabilized;

generate relationships based on the concepts using singular value decomposition;

rank the relationships based on various metrics; and

extract the relationships that are ranked above a particular threshold using a relationship generation module.

16. The non-transitory, computer-readable medium recited in claim 15, comprising code configured to direct a processor to generate concepts from the pre-processed documents using singular value decomposition by:

creating a matrix to generate concepts, said matrix having rows that represent unigrams or multi-grams and columns that represent documents; and

expressing the matrix as a product of three matrices, including a diagonal matrix of singular values ordered in descending order, a matrix representing terms, and a matrix representing documents, using singular value decomposition.

17. The non-transitory, computer-readable medium recited in claim 15, comprising code configured to direct a processor to generate relationships based on the concepts using singular value decomposition by:

creating a matrix to generate relationships, said matrix having rows that represent single words, concepts, and triples and columns that represent documents; and

expressing the matrix another as a product of three matrices using singular value decomposition.

18. The non-transitory, computer-readable medium recited in claim 15, wherein the various metrics include another term weight, another distance metric, a number of elementary words in the concepts connected by the relationship, or a TFIDF weight of the concepts.

19. The non-transitory, computer-readable medium recited in claim 15, wherein seed concepts are provided or a mind map of concepts and relationships is rendered.

20. The non-transitory, computer-readable medium recited in claim 15, wherein the relationship is expressed by one or more verbs, or a verb and a preposition, or a noun and a preposition, or any other pattern known for relationships.