Text Mining with MATLAB® / by Rafael E. Banchs.

Format:

Book

Author/Creator:

Banchs, Rafael E., Author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Language:

English

Subjects (All):

Data mining.

Information storage and retrieval systems.

Computer software.

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Mathematical Software.

Local Subjects:

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Mathematical Software.

Physical Description:

1 online resource (XII, 475 pages) : 86 illustrations, 85 illustrations in color.

Edition:

2nd ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-030-87695-1

9783030876951

Access Restriction:

Restricted for use by site license.