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Method and apparatus for measuring similarity among electronic documents

Patent 6990628 Issued on January 24, 2006. Estimated Expiration Date: Icon_subject June 14, 2019. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.

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Inventors

Assignee

Application

No. 09333121 filed on 06/14/1999

US Classes:

715/500, PRESENTATION PROCESSING OF DOCUMENT715/501.1, Hypermedia707/3, Query processing (i.e., searching)707/6Pattern matching access

Examiners

Primary: Bashore, William

Attorney, Agent or Firm

International Classes

G06F 15/00
G06F 17/00
G06F 17/21

Abstract

A method and apparatus are provided for determining when electronic documents stored in a large collection of documents are similar to one another. A plurality of similarity information is derived from the documents. The similarity information may be based on a variety of factors, including hyperlinks in the documents, text similarity, user click-through information, similarity in the titles of the documents or their location identifiers, and patterns of user viewing. The similarity information is fed to a combination function that synthesizes the various measures of similarity information into combined similarity information. Using the combined similarity information, an objective function is iteratively maximized in order to yield a generalized similarity value that expresses the similarity of particular pairs of documents. In an embodiment, the generalized similarity value is used to determine the proper category, among a taxonomy of categories in an index, cache or search system, into which certain documents belong.

Other References

  • Hermann Kaindl, Stefan Kramer, Luis Miguel Afonso, Combining Structure Search and Content Search for the World-Wide Web, Proceedings of the Seventh ACM Conference on Hypertext and Hypermedia, pp. 217-224 (1998).
  • Ron Weiss, Bienvenido VĂ©lez, Mark A. Sheldon, HyPursuit: A Hierarchical Network Search Engine That Exploits Content-Link Hypertext Clustering, Proceedings of the Seventh ACM Conference on Hypertext, pp. 180-193 (1996).
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