Text Mining with MATLAB®

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Text Mining with MATLAB provides a comprehensive introduction to text mining using MATLAB. It’s 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 first part provides an introduction to basic procedures for handling and operating with text strings. Then, it reviews major mathematical modeling approaches. Statistical and geometrical models are also described along with main dimensionality reduction methods. Finally, it presents some specific applications such as document clustering, classification, search and terminology extraction.

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.

Author(s): Rafael E. Banchs (auth.)
Edition: 1
Publisher: Springer-Verlag New York
Year: 2013

Language: English
Pages: 356
Tags: Data Mining and Knowledge Discovery; Math Applications in Computer Science; Information Storage and Retrieval

Front Matter....Pages i-xi
Introduction....Pages 1-12
Front Matter....Pages 13-13
Handling Textual Data....Pages 15-32
Regular Expressions....Pages 33-48
Basic Operations with Strings....Pages 49-75
Reading and Writing Files....Pages 77-110
Front Matter....Pages 111-111
Basic Corpus Statistics....Pages 113-144
Statistical Models....Pages 145-173
Geometrical Models....Pages 175-203
Dimensionality Reduction....Pages 205-234
Front Matter....Pages 235-235
Document Categorization....Pages 237-276
Document Search....Pages 277-311
Content Analysis....Pages 313-347
Back Matter....Pages 349-355