Springer celebrates 175 years of publishing excellence! Join us >>

Texts in Computer Science

Fundamentals of Predictive Text Mining

Authors: Weiss, Sholom M., Indurkhya, Nitin, Zhang, Tong

  • Presents a comprehensive, practical and easy-to-read introduction to text mining
  • Updated and expanded with new content on deep learning, graph models, mining social media, and errors and pitfalls in big data evaluation
  • Includes chapter summaries, classroom-tested exercises, and several descriptive case studies
see more benefits

Buy this book

eBook $59.99
price for USA (gross)
  • ISBN 978-1-4471-6750-1
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $79.99
price for USA
  • ISBN 978-1-4471-6749-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $79.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: December 15, 2016
  • ISBN 978-1-4471-7113-3
  • Free shipping for individuals worldwide
About this Textbook

This successful textbook on predictive text mining offers a unified perspective on a rapidly evolving field, integrating topics spanning the varied disciplines of data science, machine learning, databases, and computational linguistics. Serving also as a practical guide, this unique book provides helpful advice illustrated by examples and case studies. This highly anticipated second edition has been thoroughly revised and expanded with new material on deep learning, graph models, mining social media, errors and pitfalls in big data evaluation, Twitter sentiment analysis, and dependency parsing discussion. The fully updated content also features in-depth discussions on issues of document classification, information retrieval, clustering and organizing documents, information extraction, web-based data-sourcing, and prediction and evaluation. Features: includes chapter summaries and exercises; explores the application of each method; provides several case studies; contains links to free text-mining software.

About the authors

Dr. Sholom M. Weiss is a Professor Emeritus of Computer Science at Rutgers University, a Fellow of the Association for the Advancement of Artificial Intelligence, and co-founder of AI Data-Miner LLC, New York.

Dr. Nitin Indurkhya is faculty member at the School of Computer Science and Engineering, University of New South Wales, Australia, and the Institute of Statistical Education, Arlington, VA, USA. He is also a co-founder of AI Data-Miner LLC, New York.

Dr. Tong Zhang is a Professor of Statistics and Biostatistics at Rutgers University.

Reviews

“Fundamentals of predictive text mining is a second edition that is designed as a textbook, with questions and exercises in each chapter. … The book can be used with data mining software for hands-on experience for students. … The book will be very useful for people planning to go into this field or to learn techniques that could be used in a big data environment.” (S. Srinivasan, Computing Reviews, February, 2016)


Table of contents (9 chapters)

  • Overview of Text Mining

    Weiss, Sholom M. (et al.)

    Pages 1-12

  • From Textual Information to Numerical Vectors

    Weiss, Sholom M. (et al.)

    Pages 13-39

  • Using Text for Prediction

    Weiss, Sholom M. (et al.)

    Pages 41-79

  • Information Retrieval and Text Mining

    Weiss, Sholom M. (et al.)

    Pages 81-96

  • Finding Structure in a Document Collection

    Weiss, Sholom M. (et al.)

    Pages 97-118

Buy this book

eBook $59.99
price for USA (gross)
  • ISBN 978-1-4471-6750-1
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $79.99
price for USA
  • ISBN 978-1-4471-6749-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $79.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: December 15, 2016
  • ISBN 978-1-4471-7113-3
  • Free shipping for individuals worldwide
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Fundamentals of Predictive Text Mining
Authors
Series Title
Texts in Computer Science
Copyright
2015
Publisher
Springer-Verlag London
Copyright Holder
Springer-Verlag London
eBook ISBN
978-1-4471-6750-1
DOI
10.1007/978-1-4471-6750-1
Hardcover ISBN
978-1-4471-6749-5
Softcover ISBN
978-1-4471-7113-3
Series ISSN
1868-0941
Edition Number
2
Number of Pages
XIII, 239
Number of Illustrations and Tables
115 b/w illustrations
Topics