New Edition – Introduction to Data Mining with Case Studies

The field of data mining provides techniques for automated discovery of valuable information from the accumulated data of computerized operations of enterprises. This book offers a clear and comprehensive introduction to both data mining theory and practice. It is written primarily as a textbook for the students of computer science, management, computer applications, and information technology.

The book ensures that the students learn the major data mining techniques even if they do not have a strong mathematical background. The techniques include data pre-processing, association rule mining, supervised classification, cluster analysis, web data mining, search engine query mining, data warehousing and OLAP. To enhance the understanding of the concepts introduced, and to show how the techniques described in the book are used in practice, each chapter is followed by one or two case studies that have been published in scholarly journals. Most case studies deal with real business problems (for example, marketing, e-commerce, CRM). Studying the case studies provides the reader with a greater insight into the data mining techniques.

The book also provides many examples, review questions, multiple choice questions, chapter-end exercises and a good list of references and Web resources especially those which are easy to understand and useful for students. A number of class projects have also been included.

Preface • Preface to the Second Edition • Preface to the First Edition

Chapter 1             Introduction

Chapter 2             Data understanding and Data Preparation

Chapter 3             Association Rules Mining

Chapter 4             Classification

Chapter 5             Cluster Analysis

Chapter 6             Web Data Mining

Chapter 7             Search Engines and Query Mining

Chapter 8             Data Warehousing

Chapter 9             Online Analytical Processing (OLAP)

Chapter 10           Information Privacy and Data Mining

Answers to Multiple Choice Questions

Index

G.K. GUPTA, Ph.D. from Monash University, is currently Adjunct Professor of Computer Science at Monash University, Clayton, Australia. He has more than 35 years of distinguished career in academic management as well as in information technology education, research and professional activities. He began his academic career at Monash University and subsequently moved to James Cook University as Foundation Professor and Head to establish a new department of computer science. He later served as Dean of the School of Information Technology at Bond University, Deputy Dean and then Acting Dean of the Faculty of Information Technology at Monash University.

He received his Master’s in computer science from the University of Waterloo and his Bachelor’s degree in engineering from the University of Roorkee (now the Indian Institute of Technology Roorkee). He was seconded by the Australian Government to the Asian Institute of Technology in Bangkok for two years. He also served at the University of Illinois Urbana-Champaign, Bell Laboratories in New Jersey, the International University in Germany, and VIT University, Vellore.

Professor Gupta is a Fellow of the Association of Computing Machinery (ACM), a Fellow of the Australian Computer Society (ACS) and a Senior Member of the IEEE. He is also the author of the book Database Management Systems.