CS290D Advanced Data Mining

CS290D - Advanced Data Mining

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Abstract: Advanced course which introduces data mining concepts, principles and algorithms. Topics include sequential pattern analysis, stream data mining, mining complex types of data, multi-relational data mining, spatiotemporal data mining, social network analysis, text mining, link analysis, data mining applications (bioinformatics, security, the Web, software engineering, etc.) and trends in data mining.

Each student is expected to write reviews (two papers) every week, present one paper and lead the discussion (45 mins) after his/her presentation, and complete a project.

Prerequisites: CS130

Enrollment Code: 50914, Instructor: Prof. Xifeng Yan , Email: xyan at cs.ucsb.edu

Time: TBD, Location: TBD Office Hour: TBD

TA: TBD, Location: TBD Office Hours: TBD

Grading: Your grade will be derived from paper reviews (30%), a class presentation (20%), and the project (50%).

Text Books (not required, optional): (1) J. Han and M. Kamber, Data Mining: Concepts and Techniques, 2nd ed., Morgan Kaufmann, 2006; (2) C. Bishop, Pattern Recognition and Machine Learning, Springer 2007; (3) S. Theodoridis and K. Koutroumbas, Pattern Recognition, Fourth Edition, 2008