Mining the World Wide Web

An Information Search Approach

  • George Chang
  • Marcus J. Healey
  • James A. M. McHugh
  • Jason T. L. Wang

Part of the The Information Retrieval Series book series (INRE, volume 10)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Information Retrieval on the Web

    1. Front Matter
      Pages 1-1
    2. George Chang, Marcus J. Healey, James A. M. McHugh, Jason T. L. Wang
      Pages 3-18
    3. George Chang, Marcus J. Healey, James A. M. McHugh, Jason T. L. Wang
      Pages 19-34
    4. George Chang, Marcus J. Healey, James A. M. McHugh, Jason T. L. Wang
      Pages 35-50
    5. George Chang, Marcus J. Healey, James A. M. McHugh, Jason T. L. Wang
      Pages 51-63
  3. Data Mining on the Web

    1. Front Matter
      Pages 65-65
    2. George Chang, Marcus J. Healey, James A. M. McHugh, Jason T. L. Wang
      Pages 67-80
    3. George Chang, Marcus J. Healey, James A. M. McHugh, Jason T. L. Wang
      Pages 81-92
    4. George Chang, Marcus J. Healey, James A. M. McHugh, Jason T. L. Wang
      Pages 93-104
    5. George Chang, Marcus J. Healey, James A. M. McHugh, Jason T. L. Wang
      Pages 105-115
  4. A Case Study in Environmental Engineering

    1. Front Matter
      Pages 117-117
    2. George Chang, Marcus J. Healey, James A. M. McHugh, Jason T. L. Wang
      Pages 119-136
  5. Back Matter
    Pages 137-170

About this book

Introduction

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.

Keywords

artificial intelligence cognition computer science data mining data warehouse database information information retrieval information system intelligence learning machine learning pattern recognition visualization web mining

Authors and affiliations

  • George Chang
    • 1
  • Marcus J. Healey
    • 2
  • James A. M. McHugh
    • 3
  • Jason T. L. Wang
    • 3
  1. 1.Kean UniversityUnionUSA
  2. 2.MobilocityNew YorkUSA
  3. 3.New Jersey Institute of TechnologyNewarkUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-1639-2
  • Copyright Information Kluwer Academic Publishers 2001
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-5654-7
  • Online ISBN 978-1-4615-1639-2
  • Series Print ISSN 1387-5264
  • About this book