Information search using knowledge agents

• US 6,636,848 B1
• Filed: 07/06/2000
• Issued: 10/21/2003
• Est. Priority Date: 05/31/2000
• Status: Expired due to Term

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Carmel, David, Aridor, Yariv, Lempel, Ronny, Herscovici, Michael, Soffer, Aya, Maarek-Smadja, Yoelle
• Primary Examiner(s): Metjahic, Safet
• Assistant Examiner(s): THAI, HANH B
• Application Number:
  US09/610,705
• Time in Patent Office: 1,202 Days
• Field of Search: 707/1-5, 707/6
• US Class Current: 707/728
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9532 Query formulation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99936 Pattern matching access

Abstract

A method for searching a corpus of documents, such as the World Wide Web, includes defining a knowledge domain and identifying a set of reference documents in the corpus pertinent to the domain. Upon inputting a query, the corpus is searched using the set of reference documents to find one or more of the documents in the corpus that contain information in the domain relevant to the query. The set of reference documents is updated with the found documents that are most relevant to the domain. The updated set is used in searching the corpus for information in the domain relevant to subsequent queries.

Claims

1. A method for searching a corpus of linked documents containing terms, comprising:

defining a knowledge domain;

identifying a set of reference documents in the corpus pertinent to the domain;

inputting a search query;

searching the corpus to find one or more of the documents in the corpus that contain information relevant to the query;

evaluating a textual resemblance between the found documents and the reference documents so as to assign respective textual scores to the found documents;

assessing links between the found documents and the reference documents so as to assign respective topological scores to the found documents; and

ranking the found documents with respect to their relevance to the domain responsive to the textual scores and the topological scores.

2. The method according to claim 1, wherein evaluating the textual resemblance comprises assessing, for each of a plurality of the terms in the found documents, a respective frequency of occurrence in the reference documents.

3. The method according to claim 1, wherein the documents comprise World Wide Web pages, and wherein assessing the links comprises generating a graph of the links between the pages and calculating authority weights of the nodes of the graph.

4. Apparatus for searching a corpus of linked documents containing terms, comprising:

a memory, adapted to store an identification of a set of reference documents in the corpus pertinent to a predefined knowledge domain; and

a search processor, which responsive to receiving a query as input, is adapted to search the corpus to find one or more of the documents in the corpus that contain information relevant to the query, to evaluate a textual resemblance between the found documents and the reference documents so as to assign respective textual scores to the found documents, to assess links between the found documents and the reference documents so as to assign respective topological scores to the found documents, and to rank the found documents with respect to their relevance to the domain responsive to the textual scores and the topological scores.

5. A computer software product for searching a corpus of documents, the product comprising a computer-readable medium in which program instructions are stored, which instructions, when read by a computer, cause the computer to receive a definition of a knowledge domain and an identification of a set of reference documents in the corpus pertinent to the domain, and further cause the computer, responsive to a query, to search the corpus to find one or more of the documents in the corpus that contain information relevant to the query, to evaluate a textual resemblance between the found documents and the reference documents to assign respective textual scores to the found documents, to assess links between the found documents and the reference documents to assign respective topological scores to the found documents, and to rank the found documents with respect to their relevance to the domain responsive to the textual scores and the topological scores.