CSE 8331 Fall 2006
DATA MINING
COURSE DESCRIPTION:
Data Mining has become one of the most exciting and fastest growing fields
in computer science. Data Mining refers to various techniques which can
be used to uncover hidden information (nuggets) from a database. The data
to be mined may be complex data including multimedia, spatial, and temporal.
Data Mining has evolved from several areas including:
databases, artificial intelligence, algorithms information retrieval, and
statistics.
This course is designed to provide graduate students with a solid understanding
of data mining concepts and tools.
In addition, related concepts such as data warehousing and OLAP will be
covered.
The course will be taught from a database perspective. CSE5330 or database
experience
is recommended as a prerequisite.
Book:
Data Mining Introductory and Advanced Topics
by Margaret H. Dunham
Prentice Hall, 2003
Book Web Page
Class Notes
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Available from Book Web site
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Example 4.9
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Gain vs. Gain-Ratio
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Excerpt from Classification and Regression Trees by leo Breiman, Jerome H. Friedman, Richard A. Olshen, and Charles J. Stone
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Derivation of weight change calculation for gradient descent
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Similarity Measures
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Significant Usage Patterns; WebKDD 2005
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Extensible Markov Model; ICDM 2004
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"Data Mining and Machine Learning in Time Series Databases," ICDM '04 tutorial,
by Dr. Eamonn Keogh
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"Time Series Similarity
Measures" KDD '00 Tutorial, by Dimitrios Gunopulos and Gautam Das
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"Support Vector and kernal Machines" by Nello Cristianini, ICML 2001 Tutorial.
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"Support-Vector Networks" by Corina Cortes and Vladimir Vapnik, Machine Leraning, 20, pp 273-297, 1995.
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"Support Vector Machines" by Marti A. Hearst, IEEE Intelligent Systems, pp 18-28, July/August 1998.
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"Markov Chains - a Short Summary" by Franco Davoli.
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"Data Stream Mining with Extensible Markov Model" Yu Meng
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miRNA Prediction
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Visualization of DNA/RNA Structure using Temporal CGRs
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Text Mining Tutorial, by Marko Grobelnik and Dunja Mladenic, IJCAI-2003 Workshop on Text Mining and Link-Analysis
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Color-Texture Analysis for Content-Based Image Retrieval, by Anh-Minh Hoang
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Tutorial Graph Based Image Segmentation by Jianbo Shi, David Martin, Charless Fowlkes, and Eitan Sharon
Homework
Projects
Current Events:
Resources:
Tools:
Introduction:
Visualization:
Related Topics:
DM Technqiues:
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Genetic Algorithms:
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Decision Trees:
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Neural Networks:
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Clustering:
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Text Mining:
Image Mining: