Introduction to Data Mining with case studies (Record no. 294350)

MARC details
000 -LEADER
fixed length control field 02687nam a2200169Ia 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788120330535
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.74 GUP-I
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name G.K. Gupta
245 ## - TITLE STATEMENT
Title Introduction to Data Mining with case studies
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New Delhi
Name of publisher, distributor, etc. Prentice-Hall of India
Date of publication, distribution, etc. 2006
300 ## - PHYSICAL DESCRIPTION
Extent xvii, 457 pages : illustrations ; 24 cm
500 ## - GENERAL NOTE
General note "Easter economy edition"--Cover.
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Preface. 1. Introduction. CASE STUDY 1A: Data Mining Techniques for Optimizing Inventories for Electronic Commerce. CASE STUDY 1B: Crime Data Mining: A General Framework and Some Examples. 2. Association Rules Mining. CASE STUDY 2: Mining Customer Value: From Association Rules to Direct Marketing. 3. Classification. CASE STUDY 3A: KDD Insurance Risk Assessment: A Case Study. CASE STUDY 3B: A Data Mining Approach for Retailing Bank Customer Attrition Analysis. 4. Cluster Analysis. CASE STUDY 4: Efficient Clustering of Very Large Document Collections. 5. Web Data Mining. CASE STUDY 5: Lessons and Challenges from Mining Retail E-Commerce Data. 6. Search Engines. CASE STUDY 6: The Anatomy of a Large-Scale Hypertextual Web Search Engine. 7. Data Warehousing. CASE STUDY 7: Data Warehouse Governance: Best Practices at Blue Cross and Blue Shield of North Carolina. 8. Online Analytical Processing (OLAP). CASE STUDY 8: Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs. 9. Information Privacy and Data Mining. CASE STUDY 9: Privacy Conflicts in CRM Services for Online Shops: A Case Study. Index.
520 ## - SUMMARY, ETC.
Summary, etc. The field of data mining provides techniques for automated discovery of most 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 students of computer science, management, computer applications, and information technology. The book ensures that students are exposed to all major data mining techniques without the mathematical rigour that one would prefer to use. 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. Studying case studies will provide the reader with a lot of insight into data mining. The book also provides many examples, end-of-chapter exercises, and a good list of references and Web resources especially those which are easy to understand and useful for students.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data mining. Data mining -- Case studies.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Barcode Date last seen Date last checked out Price effective from Koha item type
        Dept. of Computational Biology and Bioinformatics Dept. of Computational Biology and Bioinformatics Processing Center 01/09/2015 1 005.74 GUP-I DCB966 18/01/2024 18/01/2024 19/07/2019 Book