ADVANCED DATA MINING: PRINCIPLES, ALGORITHMS, and APPLICATIONS

A 310, Computing Center Building, Fudan University

July 14-18, 2008

The course introduces the principles, algorithms, and applications of advanced data mining, including algorithms, methods, implementations and applications of classification, clustering, association and correlation analysis, multidimensional and OLAP analysis, mining sequential and structured data, stream data, text data, Web data, spatiotemporal data, biomedical data and other forms of complex data.

Slides: http://www.cs.uiuc.edu/homes/hanj/dragon08/index.htm

MAJOR TOPICS:
1.General overview of data mining
2.Advanced data integration and preprocessing
3.Data warehouse, data cube, OLAP and multidimensional analysis
4.Frequent pattern and correlation analysis
5.Classification and predictive modeling
6.Cluster analysis
7.Mining sequence and time-series data
8.Mining graphs and structured patterns
9.Link analysis and mining information networks
10.Stream data mining
11.Mining spatial, spatiotemporal, RFID data, trajectories, and moving objects
12.Mining multimedia, text, and web data
13.Data mining applications: Software engineering and bioinformatics
14.Other issues on data mining: visual data mining and privacy-preserving data mining
15.Research frontiers and social impacts of data mining