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Introduction to Data Mining and its Applications

By: Contributor(s): Material type: TextTextPublication details: New Delhi Springer 2009Description: xxii, 828p. 24 x 18 cmISBN:
  • 9788184890341
DDC classification:
  • 380.1 SUM
Summary: 1. Introduction to Data Mining Principles 2. Data Warehousing, Data Mining, and OLAP 3. Data Marts and Data Warehouse 4. Evolution and Scaling of Data Mining Algorithms 5. Emerging Trends and Applications of Data Mining 6. Data Mining Trends and Knowledge Discovery 7. Data Mining Tasks, Techniques, and Applications 8. Data Mining: an Introduction – Case Study 9. Data Mining & KDD 10. Statistical Themes and Lessons Data Mining 11. Theoretical Frameworks for Data Mining 12. Major and Privacy Issues in Data Mining and Knowledge Discovery 13. Active Data Mining 14. Decomposition in Data Mining - A Case Study 15. Data Mining System Products and Research Prototypes 16. Data Mining in Customer Value and Customer Relationship Management 17. Data Mining in Business 18. Data Mining in Sales Marketing and Finance 19. Banking and Commercial Applications 20. Data Mining for Insurance 21. Data Mining in Biomedicine and Science 22. Text and Web Mining 23. Data Mining in Information Analysis and Delivery 24. Data Mining in Telecommunications and Control 25. Data Mining in Security
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Reference Reference Raj Kumar Goel Institute of Technology AIML (Artificial Intelligence and Machine Learning) 380.1 SUM (Browse shelf(Opens below)) Not for loan 96291
Reference Reference Raj Kumar Goel Institute of Technology AIML (Artificial Intelligence and Machine Learning) 380.1 SUM (Browse shelf(Opens below)) Not for loan 96292

1. Introduction to Data Mining Principles
2. Data Warehousing, Data Mining, and OLAP
3. Data Marts and Data Warehouse
4. Evolution and Scaling of Data Mining Algorithms
5. Emerging Trends and Applications of Data Mining
6. Data Mining Trends and Knowledge Discovery
7. Data Mining Tasks, Techniques, and Applications
8. Data Mining: an Introduction – Case Study
9. Data Mining & KDD
10. Statistical Themes and Lessons Data Mining
11. Theoretical Frameworks for Data Mining
12. Major and Privacy Issues in Data Mining and Knowledge Discovery
13. Active Data Mining
14. Decomposition in Data Mining - A Case Study
15. Data Mining System Products and Research Prototypes
16. Data Mining in Customer Value and Customer Relationship Management
17. Data Mining in Business
18. Data Mining in Sales Marketing and Finance
19. Banking and Commercial Applications
20. Data Mining for Insurance
21. Data Mining in Biomedicine and Science
22. Text and Web Mining
23. Data Mining in Information Analysis and Delivery
24. Data Mining in Telecommunications and Control 25. Data Mining in Security

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