Text Mining Application Programming / Edition 1

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Text mining offers a way for individuals and corporations to exploit the vast amount of information available on the Internet. Text Mining Application Programming teaches developers about the problems of managing unstructured text, and describes how to build tools for text mining using standard statistical methods from Artificial Intelligence and Operations Research. These tools can be used for a variety of fields, including law, business, and medicine. Key topics covered include, information extraction, clustering, text categorization, searching the Web, summarization, and natural language query systems. The book explains the theory behind each topic and algorithm, and then provides a practical solution implementation with which developers and students can experiment. A wide variety of code is also included for developers to build their own custom solutions. After reading through this book developers will be able to tap into the bevy information available online in ways they never thought possible and students will have a thorough understanding of the theory and practical application of text mining.

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Product Details

  • ISBN-13: 9781584504603
  • Publisher: Cengage Learning
  • Publication date: 5/4/2006
  • Series: Charles River Media Programming Series
  • Edition description: BK&CD-ROM
  • Edition number: 1
  • Pages: 412
  • Sales rank: 822,493
  • Product dimensions: 9.02 (w) x 7.38 (h) x 1.03 (d)

Meet the Author

Manu Konchady (Oakton,VA) is a consultant working on open source text mining software. Previously, he worked at Mitre Corp. where he designed and developed software to mine the Internet. He received his Ph.D. in Information Technology from George Mason University and his articles have appeared in Dr. Dobb's Journal and Linux Journal.

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Table of Contents

Preface Acknowledgments Chapter 1 Introduction Chapter 2 Mathematics Background Chapter 3 Exploring Text Chapter 4 Markov Models and POS Tagging Chapter 5 Information Extraction Chapter 6 Search Engines Chapter 7 Searching the Web Chapter 8 Clustering Documents Chapter 9 Text Categorization Chapter 10 Summarization Chapter 11 Question & Answer About the CD-ROM Index

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Customer Reviews

Average Rating 5
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Sort by: Showing all of 2 Customer Reviews
  • Anonymous

    Posted August 5, 2006

    Developers will find a knowledge of Perl useful â¿¿ but not necessary â¿¿ to understand the basics and features of an excellent data mining introduction.

    Manu Konchady's Text Mining Application Programming is a detailed in-depth survey for any software programmer interested in learning how to mine the data available on the Web and from internal networks alike. From a review of text data and its characteristics and location to later chapters on navigating the Web for data and building spiders to crawl the Web, developers will find a knowledge of Perl useful â¿¿ but not necessary â¿¿ to understand the basics and features of an excellent data mining introduction.

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  • Anonymous

    Posted November 11, 2009

    No text was provided for this review.

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