Mining the World Wide Web: An Information Search Approach / Edition 1

Mining the World Wide Web: An Information Search Approach / Edition 1

by George Chang, Marcus Healey, James A. M. McHugh, T.L. Wang
     
 

ISBN-10: 0792373499

ISBN-13: 9780792373490

Pub. Date: 07/31/2001

Publisher: Springer US

Mining the World Wide Web: An Information Search Approach explores the concepts and techniques of Web mining, a promising and rapidly growing field of computer science research. Web mining is a multidisciplinary field, drawing on such areas as artificial intelligence, databases, data mining, data warehousing, data visualization, information retrieval, machine

Overview

Mining the World Wide Web: An Information Search Approach explores the concepts and techniques of Web mining, a promising and rapidly growing field of computer science research. Web mining is a multidisciplinary field, drawing on such areas as artificial intelligence, databases, data mining, data warehousing, data visualization, information retrieval, machine learning, markup languages, pattern recognition, statistics, and Web technology. Mining the World Wide Web presents the Web mining material from an information search perspective, focusing on issues relating to the efficiency, feasibility, scalability and usability of searching techniques for Web mining.
Mining the World Wide Web is designed for researchers and developers of Web information systems and also serves as an excellent supplemental reference to advanced level courses in data mining, databases and information retrieval.

Product Details

ISBN-13:
9780792373490
Publisher:
Springer US
Publication date:
07/31/2001
Series:
Information Retrieval Series, #10
Edition description:
2001
Pages:
170
Product dimensions:
6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

List of Figures. List of Tables. Preface. Acknowledgments. Part I: Information Retrieval on the Web. 1. Keyword-Based Search Engines. 2. Query-Based Search Systems. 3. Mediators and Wrappers. 4. Multimedia Search Engines. Part II: Data Mining on the Web. 5. Data Mining. 6. Text Mining. 7. Web Mining. 8. Web Crawling Agents. Part III: A Case Study in Environmental Engineering. 9. Envirodaemon. References. Index.

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