PHI

                                   PHI Learning EEE books ebooks Delhi India                                    Helping Teachers to Teach and Students to Learn

 
EEE: Eastern Economy Editions         
Search: 
 
Home > PHI Learning > Introduction To Data Mining With Case Studies
 
INTRODUCTION TO DATA MINING WITH CASE STUDIES, SECOND EDITION By Gupta, G. K. || 978-81-203-4326-9 || PHI Learning
INTRODUCTION TO DATA MINING WITH CASE STUDIES 

INTRODUCTION TO DATA MINING WITH CASE STUDIES
 GUPTA, G. K.
PRINT EDITION PAGES: 508
Edition: SECOND EDITION
ISBN: 978-81-203-4326-9
Pages: 508
Binding: Paper Back
 
EBOOK PRICE: R450.00
NOW! Available in: R 383.00
  About ebooks and how to download them
 
Email
Print Brochure
 
  Book Reviews
 
Rate this book     Empty Star Empty Star Empty Star Empty Star Empty Star
 
Average Rating
Full Star Full Star Half Star Empty Star Empty Star

 2.5

 
(Based on 17 ratings)
 
 
5 star
1
4 star
3
3 star
2
2 star
9
1 star
2
 

About The Book
Description:

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 association rule mining, supervised classification, cluster analysis, web data 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, short answer 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.


Contents:
Preface • Preface to the First Edition
Chapter 1 INTRODUCTION
Chapter 2 ASSOCIATION RULES MINING
Chapter 3 CLASSIFICATION
Chapter 4 CLUSTER ANALYSIS
Chapter 5 WEB DATA MINING
Chapter 6 SEARCH ENGINES
Chapter 7 DATA WAREHOUSING
Chapter 8 ONLINE ANALYTICAL PROCESSING (OLAP)
Chapter 9 INFORMATION PRIVACY AND DATA MINING
Answers to Multiple Choice Questions
Index