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

Text Mining (eBook, PDF)

Predictive Methods for Analyzing Unstructured Information

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 237
• Erscheinungstermin: 8. Januar 2010
• Englisch
• ISBN-13: 9780387345550
• Artikelnr.: 37287100

Autorenporträt

Sholom M. Weiss, IBM,T.J.Watson Research Center, Yorktown Heights, NY, USA / Nitin Indurkhya, University of New South Wales, Five Dock, NSW, Australia / Tong Zhang, IBM,T.J.Watson Research Center, Yorktown Heights, NY, USA / Fred Damerau, (formerly at IBM, Pace University)

Inhaltsangabe

Overview of Text Mining.- From Textual Information to Numerical Vectors.- Using Text for Prediction.- Information Retrieval and Text Mining.- Finding Structure in a Document Collection.- Looking for Information in Documents.- Case Studies.- Emerging Directions.