Research mode for a knowledge base search and retrieval system

• US 5,953,718 A
• Filed: 11/12/1997
• Issued: 09/14/1999
• Est. Priority Date: 11/12/1997
• Status: Expired due to Term

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle Corporation
• Inventors: Wical, Kelly
• Primary Examiner(s): Black, Thomas G.
• Assistant Examiner(s): Mizrahi, Diane D.
• Application Number:
  US08/967,774
• Time in Patent Office: 671 Days
• Field of Search: 707/1-7, 707/104, 707/101, 704/1, 704/10, 706/45, 600/509, 600/301, 40/38
• US Class Current: 1/1
• 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 16/345 Summarisation for human users
• CPC Class Codes: Y10S 707/99931 Database or file accessing
• CPC Class Codes: Y10S 707/99932 Access augmentation or optimizing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99937 Sorting
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

A research mode in a search and retrieval system generates a research document that infers an answer to a query from multiple documents. The search and retrieval system includes point of view gists for documents to provide a synopsis for a corresponding document with a slant toward a topic. To generate a research document, the search and retrieval system processes a query to identify one or more topics related to the query, selects document themes relevant to the query, and then selects point of view gists, based on the document themes, that have a slant towards the topics related to the query. A knowledge base, which includes categories arranged hierarchically, is configured as a directed graph to links those categories having a lexical, semantic or usage association. Through use of the knowledge base, an expanded set of query terms are generated, and research documents are compiled that include point of view gists relevant to the expanded set of query terms. A content processing system, which identifies the themes for a document and classifies the document themes in categories of the knowledge base, is also disclosed.

Claims

1. A method for processing a query in a search and retrieval system, said method comprising the steps of:

generating a plurality of point of view gists for at least one document, wherein each point of view gist comprises a synopsis of a corresponding document with a slant toward a topic, so that said plurality of point of view gists for a single document comprise synopses with slants toward a plurality of different topics;

processing a query, which includes at least one query term, to identify a plurality of topics related to said query; and

selecting a plurality of point of view gists from one or more documents to generate, in response to said query, a new research document, wherein said point of view gists selected comprise synopses with slants toward said topics related to said query.

2. The method as set forth in claim 1, further comprising the steps of:

storing a plurality of themes for said documents, wherein said themes define an overall content for said documents;

selecting themes relevant to said query as said topics; and

selecting documents that contain said themes selected.

3. The method as set forth in claim 2, wherein the step of storing themes for a document comprises the steps of:

processing a plurality of documents to identify said themes for a document; and

classifying said documents, including themes identified for said documents, in categories so as to relate said themes to said categories.

4. The method as set forth in claim 3, wherein the step of generating a research document further comprises the step of inferring a response to said query by selecting point of view gists from documents that comprise common subject matter to generate said research document.

5. The method as set forth in claim 2, wherein the step of generating a research document further comprises the steps of:

selecting a first document comprising a first theme related to said query;

selecting at least one additional document that comprises said first theme and at least one additional theme related to said query; and

selecting, to generate said research document, a point of view gist for said first document with a slant toward said first theme, and at least one point of view gist with a slant toward said additional theme.

6. The method as set forth in claim 1 further comprising the steps of:

storing a knowledge base that comprises a plurality categories;

storing document theme vectors that classify said documents and a plurality of themes identified for said documents in categories of said knowledge base;

mapping said query term to a category of said knowledge base;

selecting a plurality of documents classified for said category; and

selecting themes for said documents as identified in said document theme vectors.

7. The method as set forth in claim 1, further comprising the steps of:

storing a knowledge base comprising a directed graph that links terminology having a lexical, semantic or usage association;

generating an expanded set of query terms through use of said knowledge base; and

processing said query including utilizing said knowledge base to generate research documents relevant to said expanded set of query terms.

8. A method for processing a query in a search and retrieval system, said method comprising the steps of:

processing a query, which includes a plurality of query terms, to identify a plurality of topics related to said query;

selecting a plurality of documents relevant to said query; and

generating, in response to said query, a new research document comprising portions of different documents of said documents selected, wherein each portion selected for said research document satisfies a different topic related to said query so as to infer a response to said query through use of multiple documents.

9. A computer readable medium comprising a plurality of instructions, which when executed by a computer, cause the computer to perform the steps of:

generating a plurality of point of view gists for at least one document, wherein each point of view gist comprises a synopsis of a corresponding document with a slant toward a topic, so that said plurality of point of view gists for a single document comprise synopses with slants toward a plurality of different topics;

processing a query, which includes at least one query term, to identify a plurality of topics related to said query; and

selecting a plurality of point of view gists from one or more documents to generate, in response to said query, a new research document, wherein said point of view gists selected comprise synopses with slants toward said topics related to said query.

10. The computer readable medium as set forth in claim 9, further comprising the steps of:

storing a plurality of themes for said documents, wherein said themes define an overall content for said documents;

selecting themes relevant to said query as said topics; and

selecting documents that contain said themes selected.

11. The computer readable medium as set forth in claim 10, wherein the step of storing themes for a document comprises the steps of:

processing a plurality of documents to identify said themes for a document; and

classifying said documents, including themes identified for said documents, in categories so as to relate said themes to said categories.

12. The computer readable medium as set forth in claim 9, further comprising the steps of:

storing a knowledge base that comprises a plurality categories;

storing document theme vectors that classify said documents and a plurality of themes identified for said documents in categories of said knowledge base;

mapping said query term to a category of said knowledge base;

selecting a plurality of documents classified for said category; and

selecting themes for said documents as identified in said document theme vectors.

13. The computer readable medium as set forth in claim 10, wherein the step of generating a research document further comprises the step of inferring a response to said query by selecting point of view gists from documents that comprise common subject matter to generate said research document.

14. The computer readable medium as set forth in claim 10, wherein the step of generating a research document further comprises the steps of:

selecting a first document comprising a first theme related to said query;

selecting at least one additional document that comprises said first theme and at least one additional theme related to said query; and

selecting, to generate said research document, a point of view gist for said first document with a slant toward said first theme, and at least one point of view gist with a slant toward said additional theme.

15. The computer readable medium as set forth in claim 9, further comprising the steps of:

storing a knowledge base comprising a directed graph that links terminology having a lexical, semantic or usage association;

generating an expanded set of query terms through use of said knowledge base; and

processing said query including utilizing said knowledge base to generate research documents relevant to said expanded set of query terms.

16. A computer readable medium comprising a plurality of instructions, which when executed by a computer, cause the computer to perform the steps of:

processing a query, which includes a plurality of query terms, to identify a plurality of topics related to said query;

selecting a plurality of documents relevant to said query; and

generating, in response to said query, a new research document comprising portions of different documents of said documents selected, wherein each portion selected for said research document satisfies a different topic related to said query so as to infer a response to said query through use of multiple documents.