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English : A System For Information Extraction And Intelligent Search Using Dynamically Acquired Background Knowledge
Abstract This paper presents a simple framework for extracting information found in publications or documents that are issued in large volumes and which cover similar concepts or issues within a given domain. The general aim of the work described, is to present a model for automatically augmenting segments of these documents with metadata using dynamically acquired background domain knowledge in order to assist users in easily locating information within these documents through a structured front end. To realize this goal, both document structure as well as dynamically acquired background knowledge, are utilized. A real life example where these ideas have been applied is also presented.
URL
Publication year 2003
Pages 157-164
Organization Name
    Central Laboratory for Agricultural Expert System (CLAES)
City Vienna
serial title International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA ‘2003)
Department Knowledge Engineering and Expert System Building Tools
Project
Author(s) from ARC
Agris Categories Documentation and information
Proposed Agrovoc information extraction;
Publication Type Conference/Workshop

 
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