Overview
- Features an in-depth and up-to-date guide to text mining with MATLAB®
- Illustrates key concepts and definitions through a series of increasingly complex examples and exercises
- Provides the reader with step-by-step instructions on how to recreate all examples and figures
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Table of contents (15 chapters)
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Front Matter
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FUNDAMENTALS
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Front Matter
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MATHEMATICAL MODELS
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Front Matter
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METHODS AND APPLICATIONS
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Front Matter
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Keywords
About this book
Text Mining with MATLAB® provides a comprehensive introduction to text mining using MATLAB. It is designed to help text mining practitioners, as well as those with little-to-no experience with text mining in general, familiarize themselves with MATLAB and its complex applications.
The book is structured in three main parts: The first part, Fundamentals, introduces basic procedures and methods for manipulating and operating with text within the MATLAB programming environment. The second part of the book, Mathematical Models, is devoted to motivating, introducing, and explaining the two main paradigms of mathematical models most commonly used for representing text data: the statistical and the geometrical approach. Eventually, the third part of the book, Techniques and Applications, addresses general problems in text mining and natural language processing applications such as document categorization, document search, content analysis, summarization, question answering, and conversational systems. This second edition includes updates in line with the recently released “Text Analytics Toolbox” within the MATLAB product and introduces three new chapters and six new sections in existing ones.
All descriptions presented are supported with practical examples that are fully reproducible. Further reading, as well as additional exercises and projects, are proposed at the end of each chapter for those readers interested in conducting further experimentation.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Text Mining with MATLAB®
Authors: Rafael E. Banchs
DOI: https://doi.org/10.1007/978-3-030-87695-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-87694-4Published: 23 October 2021
eBook ISBN: 978-3-030-87695-1Published: 21 October 2021
Edition Number: 2
Number of Pages: XII, 475
Number of Illustrations: 1 b/w illustrations, 85 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Information Storage and Retrieval, Mathematical Software