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A System For Information Extraction And Intelligent Search Using Dynamically Acquired Background Knowledge
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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.
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| URL |
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| Publication year |
2003
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| Pages |
157-164
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| Organization Name |
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| City |
Vienna
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| serial title |
International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA ‘2003)
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| Department |
Knowledge Engineering and Expert System Building Tools
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| Project |
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| Author(s) from ARC |
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| Agris Categories |
Documentation and information
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| Proposed Agrovoc |
information extraction;
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| Publication Type |
Conference/Workshop
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