CS290D - Advanced Data Mining home | schedule | project | readings 

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Abstract: The advanced course will focus on sequential pattern analysis, graph mining, link analysis, social network 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 (60 mins) after his/her presentation, and complete a research project.

Prerequisites: CS130

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

Time: Monday/Wednesday 1:00-3:00pm, Location: PHELP 1401  Office Hour:  Mon/Wed 5:00-6:00pm or by appointment

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