Overview

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.

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9781584504603

Table of Contents

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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

Author Information

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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