CS 685 Special Topics in Data mining

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CS 685 Special Topics in Data mining

• Instructor Jinze Liu
• Spring 2008

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Welcome!

• Instructor Jinze Liu
• Homepage http//www.cs.uky.edu/liuj
• Office 237 Hardymon Building
• Email liuj_at_cs.uky.edu
• Office hour by appointment

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Overview

• Time 200-315PM Tuesday and Thursday
• Place POT 145
• Credit 3
• Prerequisite none
• Preferred Database, AI, Machine Learning,
  Statistics, Algorithms

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Overview

• Textbook none
• A collection of papers in recent conferences and
  journals
• References
• Data Mining --- Concepts and techniques, by Han
  and Kamber, Morgan Kaufmann, 2006.
  (ISBN1-55860-901-6)
• Introduction to Data Mining, by Tan, Steinbach,
  and Kumar, Addison Wesley, 2006.
  (ISBN0-321-32136-7)
• Principles of Data Mining, by Hand, Mannila, and
  Smyth, MIT Press, 2001. (ISBN0-262-08290-X)
• The Elements of Statistical Learning --- Data
  Mining, Inference, and Prediction, by Hastie,
  Tibshirani, and Friedman, Springer, 2001.
  (ISBN0-387-95284-5)
• Mining the Web --- Discovering Knowledge from
  Hypertext Data, by Chakrabarti, Morgan Kaufmann,
  2003. (ISBN1-55860-754-4)

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Overview

• Grading scheme
• No homework
• No exam

Paper Presentation and discussion 40
Project 50
Attendance and participation 10
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Overview

• Paper presentation
• One per student
• Research paper(s)
• List of recommendations (will be available)
• Your own pick (upon approval)
• Three parts
• Motivation for the research
• Review of data mining methods
• Discussion
• Questions and comments from audience
• Class participation One question/comment per
  student
• Order of presentation will be arranged
  according to the topics
• Please send in your choice of paper(s) by Jan
  29th.

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Overview

• Project (due May 1st)
• One project Individual or team project
• Some suggestion will be available shortly
• You are welcome to propose your own especially
  you have a dataset for analysis.
• Due Feb 7th
• Proposal title and goal
• Survey of related work pros and cons
• Outline of approach
• Due April 1st
• Implementation update
• Due May 1st
• Implementation
• Evaluation
• Discussion and future directions

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Topics

• ScopeData Mining
• Topics
• Association Rule
• Sequential Patterns
• Graph Mining
• Clustering and Outlier Detection
• Classification and Prediction
• Regression
• Pattern Interestingness
• Dimensionality Reduction

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Topics

• Applications
• Biomedical informatics
• Bioinformatics
• Web mining
• Text mining
• Graphics
• Visualization
• Financial data analysis
• Intrusion detection

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KDD References

• Data mining and KDD (SIGKDD CDROM)
• Conferences ACM-SIGKDD, IEEE-ICDM, SIAM-DM,
  PKDD, PAKDD, etc.
• Journal Data Mining and Knowledge Discovery, KDD
  Explorations
• Database systems (SIGMOD CD ROM)
• Conferences ACM-SIGMOD, ACM-PODS, VLDB,
  IEEE-ICDE, EDBT, ICDT, DASFAA
• Journals ACM-TODS, IEEE-TKDE, JIIS, J. ACM, etc.
• AI Machine Learning
• Conferences Machine learning (ICML), AAAI,
  IJCAI, COLT (Learning Theory), etc.
• Journals Machine Learning, Artificial
  Intelligence, etc.

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KDD References

• Statistics
• Conferences Joint Stat. Meeting, etc.
• Journals Annals of statistics, etc.
• Bioinformatics
• Conferences ISMB, RECOMB, PSB, CSB, BIBE, etc.
• Journals J. of Computational Biology,
  Bioinformatics, etc.
• Visualization
• Conference proceedings InfoVis, CHI,
  ACM-SIGGraph, etc.
• Journals IEEE Trans. visualization and computer
  graphics, etc.