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Text Mining Application Programming
Text Mining Application Programming teaches software developers how to mine the vast amounts of information available on the Web, internal networks, and desktop files and turn it into usable data. The book helps developers understand the problems associated with managing unstructured text, and explains how to build your own mining tools using standard
statistical methods from information theory, artificial intelligence, and operations research. Each of the topics covered are thoroughly explained and then a practical implementation is provided.The book begins with a brief overview of text data, where it can be found, and the typical search engines and tools used to search and gather this text. It details how to build tools for extracting and using the text, and covers the mathematics behind many of the algorithms used in building these tools. From there you'll learn how to build tokens from text, construct indexes, and detect patterns in text. You'll also find methods to extract the names of people, places, and organizations from an email, a news article, or a Web page. The next portion of the book teaches you how to find information on the Web, the structure of the Web, and how to build spiders to crawl the Web. Text categorization is also described in the context of managing email. The final part of the book covers information monitoring, summarization, and a simple Question & Answer (Q&A) system. The code used in the book is written in Perl, but knowledge of Perl is not necessary to run the software. Developers with an intermediate level of experience with Perl can customize the software. Although the book is about programming, methods are explained with English-like pseudocode and the source code is provided on the CD-ROM. After reading this book, you'll be ready to tap into the bevy of information available online in ways you never thought possible.
CONTENTS:
Preface; Chapter 1: Introduction; Chapter 2:Mathematics Background; Chapter 3: Exploring Text; Chapter 4: Text Analysis; Chapter 5: Information Extraction; Chapter 6: Search Engines; Chapter 7: Searching the Web; Chapter 8: Clustering; Chapter 9: Text Categorization; Chapter 10: Summerization; Chapter 11: Question & Answer; Chapter 12: Software; Appendix A: TextMine; Appendix B: Sources; Appendix C: About the CD-ROM; Index
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