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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, Ahmed Rafea, Yasser Abdelhamid
Copyright: © 2004 |Pages: 12
ISBN13: 9781591401940|ISBN10: 1591401941|EISBN13: 9781591401957
DOI: 10.4018/978-1-59140-194-0.ch013
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MLA

El-Baltagy, Samhaa R., et al. "Using Dynamically Acquired Background Knowledge for Information Extraction and Intelligent Search." Intelligent Agents for Data Mining and Information Retrieval, edited by Masoud Mohammadian, IGI Global, 2004, pp. 196-207. https://doi.org/10.4018/978-1-59140-194-0.ch013

APA

El-Baltagy, S. R., Rafea, A., & Abdelhamid, Y. (2004). Using Dynamically Acquired Background Knowledge for Information Extraction and Intelligent Search. In M. Mohammadian (Ed.), Intelligent Agents for Data Mining and Information Retrieval (pp. 196-207). IGI Global. https://doi.org/10.4018/978-1-59140-194-0.ch013

Chicago

El-Baltagy, Samhaa R., Ahmed Rafea, and Yasser Abdelhamid. "Using Dynamically Acquired Background Knowledge for Information Extraction and Intelligent Search." In Intelligent Agents for Data Mining and Information Retrieval, edited by Masoud Mohammadian, 196-207. Hershey, PA: IGI Global, 2004. https://doi.org/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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