Fundamentals of Predictive Text Mining
Author:   Sholom M. Weiss ,  Nitin Indurkhya ,  Tong Zhang ,  Weiss
Publisher:   Springer London Ltd
Edition:   2010
Volume:   v. 41
ISBN:  

9781849962254


Pages:   226
Publication Date:   16 June 2010
Format:   Hardback
Availability:   Out of print, replaced by POD   Availability explained
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Fundamentals of Predictive Text Mining


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Author:   Sholom M. Weiss ,  Nitin Indurkhya ,  Tong Zhang ,  Weiss
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   2010
Volume:   v. 41
Dimensions:   Width: 15.60cm , Height: 1.40cm , Length: 23.40cm
Weight:   1.140kg
ISBN:  

9781849962254


ISBN 10:   1849962251
Pages:   226
Publication Date:   16 June 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD   Availability explained
We will order this item for you from a manufatured on demand supplier.

Table of Contents

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 Data Sources for Prediction: Databases, Hybrid Data and the Web Case Studies Emerging Directions

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)


Author Information

Dr. Sholom M. Weiss is a Research Staff Member with the IBM Predictive Modeling group, in Yorktown Heights, New York, and Professor Emeritus of Computer Science at Rutgers University. Dr. Nitin Indurkhya is Professor at the School of Computer Science and Engineering, University of New South Wales, Australia, as well as founder and president of data-mining consulting company Data-Miner Pty Ltd. Dr. Tong Zhang is Associate Professor at the Department of Statistics and Biostatistics at Rutgers University, New Jersey.

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