Outline of Syllabus
CE3:-Data Warehousing and Mining
Topic
Duration (Hrs)
1
Introduction & Background
06
2
Data Warehousing & OLAP
15
3
Data Mining Primitives
06
4
Association Analysis
06
5
Classification and Prediction
08
6
Clustering
06
7
Web Mining
06
8
Mining complex types of data
04
9
Applications of Data Warehousing & Mining
03
Lecture =60
Practical =60
Total class =120
Practical =60
Total class =120
BOOKS RECOMMENDED FOR READING AND REFERENCE
MAIN READING
- Jiawei Han and Micheline Kamber, "Data Mining Concepts and Techniques"
- Margaret Dunham, "Data mining: Introductory and Advanced Topics"
- Arun K Pujari, "Data Mining Techniques"
SUPPLEMENTARY READING
- T. Mitchell, "Machine Learning"
- S.M. Weiss and N. Indurkhya, "Predictive Data Mining"
- M. Jarke, M. Lenzerni, Y. Vassiliou, and P. Vassiladis, "Fundamentals of Data Warehouses"