System for predicting documents relevant to focus documents by spreading activation through network representations of a linked collection of documents
Patent 5835905 Issued on November 10, 1998. Estimated Expiration Date: 
April 9, 2017. 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.
April 9, 2017. 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.Patent ReferencesConcept matching of natural language queries with a database of document concepts System for generation of user profiles for a system for customized electronic identification of desirable objects Patent #: 5754939 InventorsAssigneeApplicationNo. 831807 filed on 04/09/1997US Classes:707/3, Query processing (i.e., searching)707/5, Query augmenting and refining (e.g., inexact access)707/102Generating database or data structure (e.g., via user interface)ExaminersPrimary: Lintz, Paul R.Attorney, Agent or FirmInternational ClassG06F 017/30AbstractA system for extracting and analyzing information from a collection of linked documents at a locality to enable categorization of documents and prediction of documents relevant to a focus document. The system obtains and analyzes topology, usage and path information from for a collection at a locality, e.g. a web locality on the world wide web. For categorization, document meta information is represented as document vectors. Predefined criteria is applied to the document vectors to create lists of "similar" types of documents. For relevance prediction, networks representing topology, usage path and text similarity amongst the documents in the collection are created. A spreading activation technique is applied to the networks starting at a focus document to predict the documents relevant to the focus document. Using category and relevance prediction information, tools can be built to enable a user to more efficiently traverse through the collection of linked documents.Other References
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