Text Mining with MATLAB®
Description
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.
Reviews / Votes
From the reviews:
"This book is ideal for professionals and students who require a basic understanding of text mining . . Starting from the point of zero-knowledge, this book presents fundamental knowledge of text mining with an easy-to-read and mathematically rigorous introduction based on statistical and geometrical models. In addition, the book summarizes the current state of research in this area with some potential applications, including document categorization, searching and content analysis. . The book is highly recommended for text mining practitioners from basic to intermediate level." (Korhan Günel, Zentralblatt MATH, Vol. 1254, 2013)
"The book offers a nice introduction to techniques and methods for text mining with MATLAB. It is recommended for MATLAB users, especially those who are familiar with writing code. . beginners will find it interesting and easy to follow. Readers interested in text mining will also find the overall matrix philosophy of MATLAB interesting. Teachers especially will find the book useful for project assignments." (Lefteris Angelis, ACM Computing Reviews, February, 2013)
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Content
Introduction.- Handling Textual Data.- Regular Expressions.- Basic Operations with Strings.- Reading and Writing Files.- Basic Corpus Statistics.- Statistical Models.- Geometrical Models.- Dimensionality Reduction.- Document Categorization.- Document Search.- Content Analysis.