ST: CS504
Advanced Topics in Data Mining Techniques
http://husky.if.uidaho.edu/DMf09/
Fall 2009

Download a flyer for this course
Course info from UI class schedule
How to get enrolled (INL employees , other students )

!!! Our first session will be held at noon on Tuesday, Aug. 25th, 2009, in CHE 301!!!

Please contact me in case of any questions.

Class period: Tuesday/Thursday 12:00pm - 1:15pm mdt
Office hours: Tuesday & Thursday, 1:15pm - 2:30pm mdt (please make an appointment)

Offered: 

    Idaho Falls (live - room TBD)
    Also as a web (online) course via     Web CT (instructor permission only). This option is for students outside of Idaho Falls and for those that cannot attend live session every time.
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Excerpt from catalog data:
CS504 ST: Advanced Topics in Data Mining Techniques:
This is an advanced topics course in Data Mining or Knowledge Discovery from Data (KDD) Systems. The course will develop a theoretical framework for major issues in data mining. Data preprocessing, reduction, data warehouse to data mining, mining frequent patterns, associations, and correlations, classification and prediction, cluster analysis, and mining stream, time-series, and sequence data mining, Bayesian classification, decision tree induction, classification by backpropagation and support vector machines, will be emphasized through optimization techniques, aspects of fuzzy logic and neural networks.
Because of the multifaceted nature of the course, only undergraduate seniors with mathematical and system maturity will be permitted to take this graduate course. Mastery of the theoretical foundations will be tested but the major goal of this course is the design and implementation of a advanced data mining system with expectations of optimal performance and flexibility. Prereq: Graduate standing or instructor permission. 

This course was offered the first time in fall 2007.

We will talk about applications ranging from intelligence gathering, to web, multimedia, marketing, and customer relationship data mining. This course has relevance to INL in particular but can fill a Special Topics need for the general student.

Class description (pdf )
Class policy (pdf )

Instructors:
Milos Manic, Ph.D.
 University of Idaho

UIIF College of Engineering at IF, UIIF CS Dept
Mailing Address:
1776 Science Center Drive, TAB Ste.#303,
Idaho Falls, ID 83402
Office:
CAES (Center for Advanced Energy Studies)
995 University Boulevard, Office # 282
Idaho Falls, ID 83415

ph. direct: 208.533.8122; fax:208.282.7950;
email: misko@uidaho.edu
url: http://www.cs.uidaho.edu/Faculty/Manic.html
url: http://husky.if.uidaho.edu
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Important links

  • Here you can find links on
    • 2009-10 UI academic calendar
    • UI courses, schedule, academic calendars, how to get enrolled, libraries, tutoring and academic assistance programs, disability support services, and many others.
  • Idaho Falls students:
    • Register for the course at the ISU/UI website: http://my.isu.edu/direct, Index Number UCS 504-41, and choose 193340.
      • INL employees: Fill out the INL Form 360.03A in Lotus Notes
  • UI academic schedule and to get enrolled

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Textbook:

  • Required material besides textbooks will be provided through web-based documentation..This course is a compilation of large number of books. It is very hard to choose a single textbook that would cover them all. I will go through each of these books in our first class.
  • Required textbooks:
    • Data Mining: Concepts and Techniques, Jiawei Han, Micheline Kamber, Hardcover: 770 pages, Publisher: Elsevier Science Ltd (The Morgan Kaufmann Series in Data Management Systems); 2nd edition (Apr 2006), ISBN-10: 1558609016, ISBN-13: 9781558609013 links 1 2.
  • Recommended books, also related more towards applications:
    • Data Mining: Practical Machine Learning Tools and Techniques, Ian H. Witten, Eibe Frank, Paperback: 525 pages, 2 edition (June 10, 2005), Publisher: Morgan Kaufmann (Morgan Kaufmann Series in Data Management Systems); ISBN-10: 0120884070, ISBN-13: 978-0120884070.
      Fuzzy Modeling and Genetic Algorithms For Data Mining and Exploration, Earl Cox, Dec 2004, Format: Paperback: 530 pages, Publisher: Elsevier Science Ltd (The Morgan Kaufmann Series in Data Management Systems), ISBN-10: 0121942759, ISBN-13: 9780121942755
      Web Data Mining and Applications in Business Intelligence and Counter-Terrorism, Bhavani Thuraisingham, ISBN-10: 0849314607, ISBN-13: 9780849314605, Hardcover, June 2003, CRC Press.
      Mining the Web: Transforming Customer Data into Customer Value, Author: Gordon Linoff, Michael J. A. Berry, Format: Paperback: 348 pages, Feb 2002, Publisher: John Wiley & Sons Inc, ISBN-10: 0471416096, ISBN-13: 9780471416098
      Mining the Web: Discovering Knowledge from Hypertext Data, Soumen Chakrabarti, Hardcover, ISBN-10: 1558607544, ISBN-13: 9781558607545, 2002, Morgan Kaufmann Pub. Mining the Web: Transforming Customer Data into Customer Value, Author: Gordon Linoff, Michael J. A. Berry, Format: Paperback: 348 pages, Feb 2002, Publisher: John Wiley & Sons Inc, ISBN-10: 0471416096, ISBN-13: 9780471416098
      Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, Author: Berry, Gordon S. Linoff, Format: Paperback, 648 pages, Edition: 2 ( Apr 2004), Publisher: John Wiley & Sons Inc, ISBN-10: 0471470643, ISBN-13: 9780471470649

  • In addition, an extensive reference material can be found at my list of references on data mining , neural networks , and intelligent control , and neurobotics and cognitive control . This is also a good place to start when you start working on your project/research paper.

Software downloads

  • Course downloads site
  • Online references, tutorials, books, examples
  • FAQ's page
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Course Material

  • Class notes (passw. req.)
  • Homework & exam assignments (passw. req.)
  • Homework should be sent to misko@uidaho.edu with the subject: "[CS504] HW1 Family_name" for homework number 1, "[CS504] HW2 Family_name" for homework number 2, etc. Please follow the instructions on deliverables and report form, specified in Class Policy and at the end of each homework. Attachments in doc, PDF, or ps format are welcome. Please compile your results into a single file only.
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Questions:

  • FAQ's page
  • SUBJECT LINE: Please, use [CS504] Family_name Question. I might be receiving over 100 emails a day. If you do not want yours to get lost, please always double check your subject line. If urgent response is needed, please use [CS504] URGENT Family_name Question. You may be taking this course under different section number, however, please do not use different course number than CS504 in your subject line.
  • SIGNATURE: Please, sign your email with Family_name, First_name Middle_name, Stud_ID: xxx-xxxxx, course section (possible section are: CS504_XX). Some of the names are fairly similar, and this way we will avoid confusion and facilitate faster correspondence.

Grades

  • You can check your grades here (passw. req.)
  • IMPORTANT: To be assigned a password, send me an email to misko@uidaho.edu with following information: full name, student ID, course section (possible section is only: CS504_xx), email, and mailing address that you want to be used for sending graded assignments.
  • NOTE: Please be aware that the correct mailing address needs to be updated on Banner too! Also, please note that starting July 1, 2003, the only official email account is your VandalMail account. Please note that I will not be replying to any other account such as yahoo, hotmail, etc.
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Course info from UI schedule page

Registrar, University of Idaho, EMAIL: registrar@uidaho.edu, MAIL: P.O. Box 444260, Moscow ID 83844-4260, PHONE: 208 885-6731
Computer Science 
INDEX   SUBJ   CRSE   SEC   CREDITS   TITLE   CAMPUS  
    START DATE   END DATE   TIMES   DAYS   BLDG   ROOM  
    INSTRUCTOR(S)   DELIVERY
METHOD  		      
193340 CS 504   41   3 ST:Advanced Topics in Data Mining Techniques   Idaho Falls (IFCHE)
    Aug 25, 2009  Dec 18, 2009  12:00 pm - 01:15 pm  TR  TBA  TBA 
    Milos Manic         
    Comments: Course Web Page: http://husky.if.uidaho.edu/  
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INL Employees - how to get enrolled

  • The INL intranet has an education programs section that gives a step by step process on what to do at http://educationprograms.inel.gov/index.aspx
    • In short, steps are:
      1. Talk with your manager about it and get approval.
      2. Complete the student registration with the university.
      3. Complete form 360.03A in Lotus Notes and submit it for manager approval
      4. Upon manager and University approval the employee will receive a copy.

Other students - how to get enrolled

 

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