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Text Mining Application Programming / Edition 1
by Manu Konchady
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
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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.
Product Details
- ISBN-13:
- 9781584504603
- Publisher:
- Cengage Learning
- Publication date:
- 05/04/2006
- Series:
- Charles River Media Programming Series
- Edition description:
- BK&CD-ROM
- Pages:
- 412
- Sales rank:
- 1,351,679
- Product dimensions:
- 9.02(w) x 7.38(h) x 1.03(d)
- Age Range:
- 3 Months
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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