Overview
- Presents techniques of preprocessing texts into structured forms
- Outlines concepts of text categorization and clustering, their algorithms, and implementation guides
- Includes advanced topics such as text summarization, text segmentation, topic mapping, and automatic text management
Part of the book series: Studies in Big Data (SBD, volume 45)
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Table of contents (16 chapters)
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Front Matter
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Part I
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Front Matter
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Part IV
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Front Matter
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Keywords
About this book
This book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections. The author provides the guidelines for implementing text mining systems in Java, as well as concepts and approaches. The book starts by providing detailed text preprocessing techniques and then goes on to provide concepts, the techniques, the implementation, and the evaluation of text categorization. It then goes into more advanced topics including text summarization, text segmentation, topic mapping, and automatic text management.
Authors and Affiliations
About the author
Dr. Taeho Jo works as a faculty member for school of game in Hongik University, South Korea. He received his PhD from University of Ottawa in 2006. His research spans text mining, neural networks, machine learning, and information retrieval. He has four years’ experience working for industrial organizations and ten years’ experience working for in academia. He has published almost 150 research papers, and he was awarded two times in the world wide biography dictionary, “Marquis Who’s Who in the World”.
Bibliographic Information
Book Title: Text Mining
Book Subtitle: Concepts, Implementation, and Big Data Challenge
Authors: Taeho Jo
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-3-319-91815-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2019
Hardcover ISBN: 978-3-319-91814-3Published: 20 June 2018
Softcover ISBN: 978-3-030-06302-3Published: 14 February 2019
eBook ISBN: 978-3-319-91815-0Published: 07 June 2018
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: XIII, 373
Number of Illustrations: 88 b/w illustrations, 148 illustrations in colour
Topics: Communications Engineering, Networks, Computational Intelligence, Data Mining and Knowledge Discovery, Information Storage and Retrieval, Big Data/Analytics