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Selected Topics in Data Mining and Networks
CSE590 - Fall 2012



  • 11/30: Project presentations: students with last name A-K (12/4), rest (12/6)
  • 10/3: Announcements will be emailed through Blackboard.
  • 9/17: Project ideas and in-class presentation slides are all posted on blackboard.
  • 9/10: Project ideas will be discussed in class --try to attend.
  • 8/28: See updated syllabus. Use blackboard to fill your spot for in-class presentation.
  • 8/28: Welcome to the class! Hope you will enjoy it :)
  • 6/26: More to come soon ...


Instructor: Leman Akoglu
  • Office: 1425 Computer Science
  • Office hours: Thur 12 noon - 1 p.m.
  • Email: invert ( @ leman)


Time / Place: Tue & Thur 8:30AM-9:50AM / 2129 CS
Recitations: TBD


Network data is available in numerous forms: social and information networks like Twitter and Facebook, blogs, Web-pages, email, phone call, biological networks, to name a few. This data is also growing and changing in time. Extracting useful knowledge from and reasoning about real-world problems, such as search and prediction,using networks makes them powerful and attractive tools to study.

This course will cover recent research on the analysis of large networks, algorithms behind network problems, and their practical applications in various diverse settings. Topics include structure and evolution of real-world networks, diffusion and propagation in networks, link analysis, community detection, anomaly and outbreak detection, and learning with networks. See syllabus for details.


There is no official textbook for the course. I will post the lecture notes and readings on course website.
Below you can find a list of recommended reading. We will follow mostly the first book in the first half of the course. See resources for other books to be aware of.

BULLETIN BOARD and other info


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Last modified by Leman Akoglu, August, 2012