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Text Mining

Text Mining Predictive Methods for Analyzing Unstructured Information

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Text Mining

Predictive Methods for Analyzing Unstructured Information

Sholom M. Weiss | Nitin Indurkhya | Tong Zhang | Fred Damerau

Computers / Data Science / Data Analytics

Text mining searches for regularities, patterns or trends in natural language text. Inspired by data mining, which discovers major patterns from highly structured databases, text mining aims to extract useful knowledge from unstructured text. This book focuses on the concepts and methods needed to expand horizons beyond structured, numeric data to automated mining of text samples. This authoritative and highly accessible text/reference, written by a team of authorities on text mining, develops the foundation concepts, principles, and methods needed to expand beyond structured, numeric data to automated mining of text samples. Researchers, computer scientists, and advanced undergraduates and graduates with work and interests in data mining, machine learning, databases, and computational linguistics will find the work an essential resource.


Publication Date: 19 November 2010
Publisher: Springer New York
Imprint: Springer
ISBN-13: 9781441929969
Format: Paperback softback
Page Count: 237

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