WPI Worcester Polytechnic Institute

Computer Science Department
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CS548 Knowledge Discovery and Data Mining 
Schedule of Classes - Spring 2012

PROF. CAROLINA RUIZ 

WARNING: Changes to this schedule may be made during the course of the semester. 
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WEEK DATE DUE TOPIC READINGS
1 Jan. 12 & 19   Introduction to KDD & Data Mining   Chp. 1 & 2, assigned papers
2 Jan. 23 & 26   Data & Data Preparation
  • Concepts, instances, attributes
  • Data preprocessing
  • Attribute selection
  •   Chp. 2 & 3
    3 Jan. 30 & Feb. 2   Data & Data Preparation (cont.)
  • Data integration
  • Data warehousing & OLAP
  • Dimensionality reduction
  •   Chp. 2 & 3, Appendix B
    4 Feb. 6 & 9 Project 1 Mining process
  • Training and Testing
  • Cross validation
  • Performance evaluation
    Project 1 presentations
  •   Chp. 4
    5 Feb. 13 & 16   Classification
  • Decision trees
  •   Chp. 4
    6 Feb. 20 & 23   Numeric Predictions
  • linear regression
  • model trees
  • regression trees
  •   Appendix D, assigned readings
    7 Feb. 27 & Mar. 1 Project 2 Association Analysis
  • association rules
    Project 2 presentations
  •   Sec. 6.1-6.3, 6.7-6.9.
    8 Mar. 12 & 15   Association Analysis (cont.)
  • association rules
  •   Chp. 6
    9 Mar. 19 & 22   Cluster Analysis
  • partitioning methods
  • hierarchical methods
  • density-based methods
  •   Chp. 8
    10 Mar. 26 & 29 Project 3 Cluster Analysis (cont.)
  • grid-based methods
  • model-based methods
    Project 3 presentations
  •   Chp. 8
    11 Apr. 2 & 5   Anomaly Detection
  • model-based methods
  • proximity-based methods
  • density-based methods
  •   Chp. 10
    12 Apr. 9 & 12 Project 4 Advanced topics
  • Visualization
  • Web mining
    Project 4 presentations
  •   assigned papers
    13 Apr. 19 & 23   Advanced topics (cont.)
  • Similarity search
  • Sequence mining
  • Multimedia data mining
  •   assigned papers
    14 Apr. 26 & 30 Project 5 Advanced topics (cont.)
  • Text mining
  • Industrial applications of data mining
  • Scientific applications of data mining
    Project 5 presentations
  •   assigned papers