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Introduction to Data Mining with case studies
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 textboo...
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| Format: | Printed Book |
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New Delhi
Prentice-Hall of India
2006
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Table of Contents:
- 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.