Using Dynamically Acquired Background Knowledge for Information Extraction and Intelligent Search

Using Dynamically Acquired Background Knowledge for Information Extraction and Intelligent Search

Samhaa R. El-Baltagy (Ministry of Agriculture and Land Reclamation, Egypt), Ahmed Rafea (Ministry of Agriculture and Land Reclamation, Egypt) and Yasser Abdelhamid (Ministry of Agriculture and Land Reclamation, Egypt)
Copyright: © 2004 |Pages: 12
DOI: 10.4018/978-1-59140-194-0.ch013
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Abstract

This chapter 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 to help users easily locate information within these documents through a structured front end. To realize this goal, both document structure and dynamically acquired background knowledge are utilized. A real life example where these ideas have been applied is also presented.

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