Text Mining with MATLAB®
Autor Rafael E. Banchsen Limba Engleză Hardback – 14 aug 2012
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.
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Specificații
ISBN-13: 9781461441502
ISBN-10: 1461441501
Pagini: 368
Ilustrații: XII, 356 p.
Dimensiuni: 155 x 235 x 33 mm
Greutate: 0.69 kg
Ediția:2013
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States
ISBN-10: 1461441501
Pagini: 368
Ilustrații: XII, 356 p.
Dimensiuni: 155 x 235 x 33 mm
Greutate: 0.69 kg
Ediția:2013
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States
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Public țintă
ResearchCuprins
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.
Recenzii
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)
“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)
Caracteristici
Features the first in-depth guide to text mining with Matlab, a powerful, yet flexible numerical computing platform and programming language Illustrates key concepts and definitions through a series of increasingly complex examples and exercises Provides the reader with step-by-step, easy-to-follow instructions on how to recreate all examples and figures presented within the book Includes supplementary material: sn.pub/extras
Notă biografică
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.
Textul de pe ultima copertă
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.
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.