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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Text Mining

Text Mining
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Author(s): Antonina Durfee (Appalachian State University, USA)
Copyright: 2008
Pages: 12
Source title: Handbook of Research on Public Information Technology
Source Author(s)/Editor(s): G. David Garson (North Carolina State University, USA)and Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-857-4.ch054

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Abstract

Massive quantities of information continue accumulating at about 1.5 billion gigabytes per year in numerous repositories held at news agencies, at libraries, on corporate intranets, on personal computers, and on the Web. A large portion of all available information exists in the form of text. Researchers, analysts, editors, venture capitalists, lawyers, help desk specialists, and even students are faced with text analysis challenges. Text mining tools aim at discovering knowledge from textual databases by isolating key bits of information from large amounts of text, identifying relationships among documents. Text mining technology is used for plagiarism and authorship attribution, text summarization and retrieval, and deception detection.

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