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Using Dynamically Acquired Background Knowledge For Information Extraction And Intelligent Search
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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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| Publication year |
2004
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| Organization Name |
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| Country |
United States
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| City |
Hershey
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| Publisher |
Name:
Idea Group Publishing
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| serial title |
Intelligent Agents for Data Mining and Information Retrieval
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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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| Book editors |
Masoud Mohammadian
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| Agris Categories |
Documentation and information
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| Publication Type |
Book / Book Chapter
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