Authors:
- Presents a comprehensive, practical and easy-to-read introduction to text mining
- Includes chapter summaries, useful historical and bibliographic remarks, and classroom-tested exercises for each chapter
- Provides several descriptive case studies that take readers from problem description to systems deployment in the real world
- Includes supplementary material: sn.pub/extras
Part of the book series: Texts in Computer Science (TCS)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
About this book
Reviews
From the reviews:
"This is a practical, up-to-date account of the various techniques for dealing intelligently with free text. It would be an invaluable resource to any advanced undergraduate student interested in information retrieval." (Patrick Oladimeji, Times Higher Education, 26 May 2011)
“This is a well-written and interesting text for information technology (IT) professionals and computer science students. It seems to address all of the topics related to the fields that, when integrated, are known as knowledge engineering. … Without a doubt, the authors’ experience in the field makes this book a successful contribution to the literature that targets the interests of the IT community and beyond.” (Jolanta Mizera-Pietraszko, ACM Computing Reviews, June, 2011)
“This well-written work, which offers a unifying view of text mining through a systematic introduction to solving real-world problems. … The uniqueness of this book is the recourse to the prediction problem, which, by providing practical advice, allows for the integration of related topics. … The book is accompanied by a software implementation of the main algorithmic practices introduced. This is the icing on the cake for both beginners and expert readers … . This is the book … I have always wanted to read.” (Ernesto D’Avenzo, ACM Computing Reviews, August, 2012)
Authors and Affiliations
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T.J. Watson Research Center, IBM Corporation, Yorktown Heights, USA
Sholom M. Weiss
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School of Computer Science &, Engineering, University of New South Wales, Sydney, Australia
Nitin Indurkhya
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Dept. Statistics, Rutgers University, Piscataway, USA
Tong Zhang
About the authors
Bibliographic Information
Book Title: Fundamentals of Predictive Text Mining
Authors: Sholom M. Weiss, Nitin Indurkhya, Tong Zhang
Series Title: Texts in Computer Science
DOI: https://doi.org/10.1007/978-1-84996-226-1
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London Limited 2010
Softcover ISBN: 978-1-4471-2565-5Published: 05 September 2012
eBook ISBN: 978-1-84996-226-1Published: 14 June 2010
Series ISSN: 1868-0941
Series E-ISSN: 1868-095X
Edition Number: 1
Number of Pages: XIV, 226
Topics: Data Mining and Knowledge Discovery, Natural Language Processing (NLP), Computer Appl. in Administrative Data Processing, Information Storage and Retrieval, Database Management