Week 1 (Aug 31, 2004):
Topics covered: Course Syllabus, Introduction to Data Warehousing and
Mining (Chapter 1 from Han's book)
Lecture 1 (ppt)
Reading
assignment: Ch 1
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Week 2:
(Sep 7, 2004):
Topics covered: Data Warehouse and OLAP Technology (Chapter 2 from Han's book)
Lecture 2 (ppt)
Reading
assignment: Ch 2
Matlab help documents/files: tutorial.m,
operations.m,
Matlab
tutorial (.ps)
Homework
1
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Week 3:
(Sep 14, 2004):
Topics covered: Data Properties (Chapter
3 from Han's book)
Lecture
3 (ppt)
Reading
assignment: Ch 3
Homework
2
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Week 4:
(Sep 21, 2004):
Topics covered: Connecting Matlab
and SQL Server, Data Properties, Association Rules (Chapter 6 from Han's book)
Lecture
4 (ppt)
Presentation by Hongbo Xie: Connecting
Matlab and SQL Server (instructions
in Word)
Quiz 1
Reading
assignment: Ch 6
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Week 5:
(Sep 28, 2004):
Topics covered: Association Rules (Chapter 6 from Han's book)
Lecture
5 (ppt)
Homework
3
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Week 6:
(Oct 05, 2004):
Topics covered: Clustering (Chapter
8 from Han's book)
Lecture
6 (ppt)
Homework
4
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Week 7: (Oct 12, 2004):
Topics covered: Decision Trees
(Chapter 7.1-7.3 from Han's book)
Lecture
7 (ppt)
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Week 8: (Oct 19, 2004):
Topics covered: Alternative
Classification Algorithms (Chapter 7 from Han's book)
Lecture
8 (ppt)
Quiz 2
Homework
5
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Week 9: (Oct 26, 2004):
Topics covered: Alternative
Classification Algorithms
About Course Projects
Instructions for Project
Proposal (Proposal is due Nov 02, in class)
Examples of paper/project
presentations:
ijcnn99,
ijcnn01,
ecai04
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Week 10: (Nov 02, 2004)
Topics covered: Mining Complex Types
of Data (Chapter 9 from Han's book)
Lecture
10 (ppt)
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Week 11: (Nov 09, 2004)
Topics covered: Mining Complex Types
of Data - Information Retrieval
Lecture
11 (ppt)
Homework
6
Class
Presentation Instructions
Useful Reading:
How
to give a bad presentation
Ian Parbery, "How
to Present a Paper in Theoretical Computer Science: A Speaker's Guide
for Students"
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Week 12: (Nov 16, 2004)
Papers to be presented during Week 12:
-
G. Das, K.-I. Lin, H. Mannila, G.
Renganathan, P. Smyth. Rule
discovery from time series. Proceedings of the 4th International
Conference of Knowledge Discovery and Data Mining, 1998
- M. Steinbach, PN. Tan, V. Kumar, S. Klooster, C. Potter, Data
Mining for the Discovery of Ocean Climate Indices, Proc of the
Fifth Workshop on Scientific Data Mining at 2nd SIAM International
Conference on Data Mining, 2002.
- GH. John, P. Langley. Static
versus dynamic sampling for data mining. In E. Simoudis, J-W.
Han, and U. Fayyad, editors, Proceedings, Second International
Conference on Knowledge Discovery and Data Mining, pages 367--370,
Menlo Park, CA, 1996. AAAI Press.
- GM. Weiss, F. Provost, Learning
When Training Data are Costly: The Effect of Class Distribution on
Tree Induction, Volume 19, 315-354, 2003.
- JL. Herlocker, JA. Konstan, A. Borchers, J. Riedl, An
Algorithmic Framework for Performing Collaborative Filtering.
SIGIR Conference, 230-237, 1999.
Homework
7
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Week 13: (Nov 30, 2004)
Papers to be presented during Week 13:
- Ali K, Stam WV, Tivo: Making Show Recommendations Using a
Distributed Collaborative Filtering Architecture, Proceedings ACM
SIGKDD International Conference on Knowledge discovery and Data
Mining, 394 - 401, Seattle, 2004. (download)
- Donoho S, Early Detection of Insider Trading in Option Markets,
Proceedings ACM SIGKDD International Conference on Knowledge
discovery and Data Mining, 420 - 429, Seattle, 2004. (download)
- Yoshida K, et al., Density-Based Spam Detector, Proceedings ACM
SIGKDD International Conference on Knowledge discovery and Data
Mining, 486 - 493, Seattle, 2004. (download)
- Han J, Pei J, Dong G, Wang K, Efficient Computation of Iceberg
Cubes With Complex Measures, Proc. 2001 ACM SIGMOD International
Conf. on Management of Data, Santa Barbara, 2001. (download)
- Keogh E, Pazzani M. An Enhanced Representation of Time Series
which Allows Fast and Accurate Classification, Clustering and
Relevance Feedback, Proceedings of the 4th International Conference
on Knowledge Discovery and Data Mining, New York, 239-241, 1998. (download)
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| Week 14
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