Rafael E. Banchs

Text Mining with MATLAB®

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-87694-4
• 2. Aufl.
• Seitenzahl: 492
• Erscheinungstermin: 23. Oktober 2021
• Englisch
• Abmessung: 235mm x 155mm x 27mm
• Gewicht: 739g
• ISBN-13: 9783030876944
• ISBN-10: 3030876942
• Artikelnr.: 62451873

Autorenporträt

Rafael E. Banchs is a senior data science manger with more than 25 years of experience in signal processing, data science and text mining applications. Rafael has a similar number of years of practical experience using the MATLAB® product and have completed multiple projects and developed applications with it. He received a PhD in Electrical Engineering from The University of Texas at Austin in 1998 and has published several papers in peer-reviewed Journals and International Conferences.

Inhaltsangabe

1. Introduction.- PART I: FUNDAMENTALS.- 2. Handling Text Data.- 3. Regular Expressions.- 4. Basic Operations with Strings.- 5. Reading and Writing Files.- 6. The Structure of Language.- PART II: MATHEMATICAL MODELS.- 7. Basic Corpus Statistics.- 8. Statistical Models.- 9. Geometrical Models.- 10. Dimensionality Reduction.- PART III: METHODS AND APPLICATIONS.- 11. Document Categorization.- 12. Document Search.- 13. Content Analysis.- 14. Keyword Extraction and Summarization.- 15. Question Answering and Dialogue.

---

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.

Rezensionen

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)