Selected Topics: Data Mining AT70'90 Comp' Sc' and Inf' Mgmt' Asian Institute of Technology

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Selected Topics Data Mining (AT70.90Comp. Sc.
and Inf. Mgmt.Asian Institute of Technology
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Course OverviewPage 1

• Instructor Dr. Sumanta Guha
• Office 104 CSIM Building
• Email guha_at_ait.ac.th
• Telephone [phone] (5714 inside AIT)
• Teaching Assistant Mr. Chansophea Chuon
• Office 204 CSIM Building
• Email Chansophea.Chuon_at_ait.ac.th
• Telephone 7378
• Credits 3(3-0)
• Prerequisite
• Officially none
• Course Website http//www.cs.ait.ac.th/guha/DM/

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Course OverviewPage 2

• Class times Mon. and Wed. 1500-1700
• (course will run over 11 weeks, which means
  we may go a little into the August semester)
• Discussion Group Yahoo group ait_csim_dm
• ( http//groups.yahoo.com/group/ait_csim_cga/
  )
• You must join the group!
• Important Students are always welcome in my
  office (provided I am not busy). Its best to
  make an appointment. Note that I am not a morning
  person.
• However, its good for everyone, if possible,
  to post questions and comments to the discussion
  group!! Then, everybody benefits from the
  interaction. Announcements by the instructor will
  always be posted to the group.
• Please check the group frequently and please
  participate in discussions !!

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Course OverviewPage 3

• Textbook (required)
• J. Han and M. Kamber (2006), Data Mining
  Concepts and Techniques, 2nd edition, Morgan
  Kaufmann.
• Brief Course Outline
• First half of course (weeks 1-6) Instructor
  presents Chs. 4-7 of Han/Kamber. You are expected
  to read Chs. 1-3 on your own.
• Second half of course (weeks 7-12) Seminar mode
  paper(s)/topic presentation by students. Groups
  of 1-2 students will present for 2hrs. each.
• Presentation area to be decided in consultation
  with instructor. Group is expected to go deep
  into the papers or topic, with background
  literature, review of state-of-the-art, important
  future problems, etc. Presentation should be in
  your own words, with added examples etc. You
  should not just walk through what others have
  done! PP slides and hand-outs will be expected.

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Course OverviewPage 4

• Objectives
• To learn the fundamental concepts of modern-day
  DM.
• To become familiar with recent DM literature. DM
  is a young field so most developments are, in
  fact, recent. Therefore, using original research
  papers as source material is not only possible,
  but advisable.
• To acquire some familiarity with practical DM
  software.

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Course OverviewPage 5

• Reference Books
• M. J. A. Berry and G. Linoff (1997), Data Mining
  Techniques For Marketing, Sales, and Customer
  Relationship Management, Wiley.
• I. H. Witten and E. Frank (2001), Data Mining
  Practical Machine Learning Tools and Techniques,
  Morgan Kaufmann.
• T. Soukup and I. Davidson (2002), Visual Data
  Mining Techniques and Tools for Data
  Visualization and Mining, Wiley.
• P. Tan, M. Steinbach and V. Kumar (2005),
  Introduction to Data Mining, Addison-Wesley.
• D. T. Larose (2006), Data Mining Methods and
  Models, Wiley.

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Course OverviewPage 6

• Grading System (tentative)
• Quizzes (two, possibly three) 60
• Presentation 40
• Enjoy the Course!
• Be enthusiastic about the material because it is
  interesting, practical, and extremely important
  in the modern day world. Our job is to help you
  learn and enjoy the experience. We will do our
  best but we also need your help.