Alex Berson and Stephen.J.Smith, “Data Warehousing, Data Mining and OLAP”,
Tata McGraw. Hill, 2004. 2. Jiawei Han and Micheline Kamber, “Data Mining ...
SRM University Department of Information Technology COURSE PLAN
LT PC 3 0 3 4
Programme : M.Tech. (Database Systems)
Year : I
Course : DB0503 – Data Mining
Faculty : D.Hemavathi
Week I II III IV V (Test-2 periods) VI
VII VIII IX, X, XI XI XII XIII, XIV XIV
Contents/Topics Need for the Subject, Course contents overview Data Warehousing – A summary Data Warehousing to Data Mining Business Context for data mining Technical Context for data mining Approaches to data mining Directed and Undirected mining Data Transformation Predictive Modeling – An Introduction Effective Predictive models Divide and Conquer Technique Oversampling
Hours Required 1 2 1 1 1 1 1 1 1 1 1 1
Reference --R2 R1, R2 R3
R3
Introduction to Mining Patterns, Associations and
1
Correlations Market Basket Analysis Frequent Pattern Mapping Sample problems based on Support, Confidence Apriori algorithm, Sample problem ECLAT algorithm, Sample problem Classification and Prediction Cluster Analysis Journal Paper Presentations
1 1 1 2 2 1 2 5
Automatic Cluster Detection Decision Trees Neural Networks Case Studies
2 3 1 3
Internet
Applications of data mining in different domains
2
R2, Internet
S.No
Seminar Topic
1.
Predictive Modeling
2.
Data Mining in Industry
Reference Books
R1, R2
Journals R2, R3
Proposed Date February 3rd week April 1st week
1. Alex Berson and Stephen.J.Smith, “Data Warehousing, Data Mining and OLAP”, Tata McGraw Hill, 2004 2. Jiawei Han and Micheline Kamber, “Data Mining : Concepts and Techniques”, Morgan Kaufmann Publishers, Second Edition, 2006 3. Berry Lin off, “Mastering Data Mining: The Art and Science of Customer Relationship Management”, John Wiley & Sons, 2001
