CMSC 828G
Principles of Data Mining
Spring 2002
Approximate Syllabus*

This syllabus shows for each class session: the topics that will be covered, the required and optional readings and any assignments that are due that day. All homework and programming assignments are due at the beginning of class.

Session Date Topic Notes Required
Reading 		Optional
Reading 		Assignment
Due Today 		slides
1
Jan 29
Introduction and Course Overview  

HMS ch. 1
How much Information is there in the World?, Michael Lesk, 1997.
Data Mining and Statistics: What’s the Connection? Jerome Freidman, 1997

  H0

handouts (6 slides/page)
ps pdf
slides (1 slide/page)
ps, pdf

2
Jan 31
Measurement and Data   HMS ch. 2    
handouts (ps pdf)
slides (ps, pdf)
3
Feb 5
Measurement and Data cont., Visualization        
handouts(ps pdf)
slides (ps, pdf)
4
Feb 7
Data Visualization

guest lecturer:
Ben Shneiderman

HMS ch 3
Inventing discovery tools: combining invormation visualization with data mining Ben Shneiderman, 2001

   
5
Feb 12
Uncertainty - random variables, statistical inference        
handouts(ps pdf)
slides (ps, pdf)
6
Feb 14
Student Dataset Presentations       P1
7
Feb 19
Uncertainty - random variables, statistical inference   HMS ch 4    
handouts(ps pdf)
slides (ps, pdf)
8
Feb 21
Data Analysis - estimators, hypothesis testing, sampling methods       H1
handouts(ps pdf)
slides (ps, pdf)
9
Feb 26
Descriptive Models: Clustering: k-means, hierarchical clustering   HMS ch 9    
handouts (ps pdf)
slides (ps, pdf)
10
Feb 28
Clustering, cont.: mixture models, EM   HMS ch 9 J. Blimes, A Gentle Introduction to the EM Algorithm (1998).  
handouts (ps pdf)
slides (ps, pdf)
11
Mar 5
Desciptive Models: graphical models        
handouts (ps pdf)
slides (ps, pdf)
12
Mar 7
Bayesian networks       H2
handouts (ps pdf)
slides (ps, pdf)
13
Mar 12
cancelled  

 


 
13
Mar 14
Bayesian networks  
  P2
handouts (ps pdf)
slides (ps, pdf)
15
Mar 19
Learning Bayesian networks        
handouts (ps, pdf)
slides (ps, pdf)
16
Mar 21
Midterm
       
spring break
17
Apr 2
Learning Bayesian Networks, cont.        
handouts (ps pdf)
slides (ps, pdf)
18
Apr 4
Recommender Systems guest lecturer
Doug Oard

Modelling Information Content Using Observable Behavior, Oard and Kim. ASiST, 2001.

Emperical analysis of predictive algorithms for collaborative filtering, Breese, Heckerman and Cadie. AAAI 1998.

  P3
handouts (ps pdf)
slides (ps, pdf)
19
Apr 9

Predictive Modelling for classification: trees, nearest neighbor, naive bayes

 

  HMS ch 10, 11    
handouts (ps pdf)
slides (ps, pdf)
20
Apr 11
Predictive Modelling, cont.        
21
Apr 16

Predictive Modelling cont.,
Finding patterns and rules

  HMS ch 13    
handouts (ps pdf)
slides (ps, pdf)
22
Apr 18

Finding patterns and rules cont.

  HMS ch 12   H3
handouts (ps pdf)
slides (ps, pdf)
23
Apr 23
Data Streams, OLAP (as time permits) guest lecturer:
Antonios Deligiannakis

Countinuous Queries Over Data Streams, S. Babu and J. Widom. SIGMOD Record, 2001

Mining High-Speed Data Streams, Geoff Hulten and Pedro Domingos. KDD2000

 

Mining Time-Changing Data Streams, Geoff Hulten, Laurie Spencer and Pedro Domingos. KDD2001  
slides (ppt)
24
Apr 25
Text Retrieval

guest lecturer:
Rebecca Hwa

Untangling Text Data Mining, Marti Hearst. ACL 1999 invited paper
E. Riloff and R. Jones, http://www-2.cs.cmu.edu/~knigam/papers/emcat-mlj99.ps in the Proceedings of AAAI-99, 1999.
K. Nigam, A. McCallum, S. Thrun, and T. Mitchell, “Text Classification from Labeled and Unlabeled Documents using EM,” in Machine Learning, 2000.
M. Grobelnik, D. Mladenic, and N. Milic-Frayling, “Text Mining as Integration of Several Related Research Areas: Report on KDD’2000 Workshop on Text Mining,” 2000.

   
slides (ppt)
25
Apr 30
Link Analysis   Link Analysis in Web Infromation Retrieval, Monika Henzinger. Bulletin of the IEEE computer Society Technical Committee on Data Engineering, 2000.   P4
handouts (ps pdf)
slides (ps, pdf)
26
May 2
Project Presentations        
27
May 7
Project Presentations       P5
28
May 9
Project Presentations       H4
29
May 14
Project Presentations
wrap-up 		      P6
handouts (ps pdf)
slides (ps, pdf)

Saturday
May 18
10:30AM - 12:30PM
Final
       

 

Key:
HMS = Hand, Mannila, Smyth, Principles of Data Mining
H = homework assignment
P = project

* This syllabus is subject to change. There are a number of readings that will be added, and the assignment dues dates are still being tuned. Please check it periodically.

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syllabus template courtesy of Doug Oard and Phillip Resnik
Last modified 03/17/2002

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