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Jožef Stefan International Postgraduate School
Statistics
2010/2011
Data Mining Courses Webpage
Courses:
Jožef Stefan IPS Bologna MSc (ICT2/IKT2):
(A) Data Mining and Knowledge Discovery / Podatkovno rudarjenje in odkrivanje zakonitosti (8/24 ct)
Jožef Stefan IPS PhD (ICT3/IKT3) Module Knowledge Technologies / Modul Tehnologije znanja:
(B) Selected techniques for tabular and relational data mining / Izbrane tehnike rudarjenja tabelaričh in večrelacijskih podatkov (3 ct)
Statistics MSc program:
(C) Data mining / Podatkovno rudarjenje (12 ct)
Special cases:
(D) Data mining / Podatkovno rudarjenje (5-6 ct)

Wednesday, 3. 11. 2010 15:15 - 17:00 Seminar I (ICT3): Knowledge Technologies - Text, web and multimedia mining
(doc. dr. Dunja Mladenić)
IPS lecture hall
17:15 - 19:00 Text, web and multimedia mining (ICT3)
(doc. dr. Dunja Mladenić)
IPS lecture hall
Wednesday, 10. 11. 2010 15:15 - 17:00
Seminar I (ICT3): Knowledge Technologies - Data Mining
(prof. dr. Nada Lavrač)
IPS lecture hall
17:15 - 19:00
Selected techniques for tabular and relational data mining (ICT3)
(prof. dr. Nada Lavrač)
IPS lecture hall
Tuesday, 23. 11. 2010
17:15 - 19:00 Data Mining and Knowledge Discovery (ICT2)
(N. Lavrač, B. Cestnik, D. Mladenić, P. Kralj Novak)
IPS lecture hall
Thursday, 25. 11. 2010 15:15 - 18:00 Practice
(dr. Petra Kralj Novak)
Orange room*
Thursday, 2. 12. 2009 15:15 - 18:00 Practice
(dr. Petra Kralj Novak)
Orange room*
Wednesday, 8. 12. 2010** 17:00 - 19:00
Statistika - Sodobni statistični pristopi - rudarjenje podatkov (in English)
(prof. dr. Nada Lavrač)
FMF, room 2.03***
Thursday, 16. 12. 2010 16:00 - 17:00 Data Mining written exam
(dr. Petra Kralj Novak)
Kolarjeva predavalnica****
17:00 - 18:00 Data Mining seminar topic presentations
(dr. Petra Kralj Novak)
Kolarjeva predavalnica****
Thursday, 3. 2. 2011 15:15 - 17:00 Data mining seminar presentations
(prof. dr. Nada Lavrač, dr. Petra Kralj Novak)
IPS lecture hall
Thursday, 16. 3. 2011 15:15 - 17:00 Text, web and multimedia mining (ICT3)
(doc. dr. Dunja Mladenić)
IPS lecture hall
* Orange room: 2nd floor of JSI main building
** For those who missed the lecture on 10.11.2010
*** Faculty of Mathematics and Physics, Jadranska 21, room 2.03
**** Kolarjeva predavalnica: ask the JSI doorman

Course materials

  • page of the part of the DATA MINING AND KNOWLEDGE DISCOVERY (ICT2) course on data preprocessing that is covered by doc. dr. Bojan Cestnik
  • Lectures: prof. dr. Nada Lavrač
  • Practice: dr. Petra Kralj Novak
    • practice notes:
      • 25.11.2010 slides: (.pdf) , 6/page (.pdf); discussion (.pdf), 6/page (.pdf)
      • 2.12.2009 slides: (.pdf) , 6/page (.pdf)
      • entropy and information gain (.pdf)
      • decision trees (.pdf)
      • naive Bayes (.pdf)
      • association rules (.pdf)
    • hands on Weka
      • classification (.pdf), 6/page (.pdf)
      • numeric prediction (.pdf), 6/page (.pdf)
      • classificarion and association rules (.pdf), 6/page (.pdf)
      • datasets (.zip)

Useful links

Course requirements:


written exam data mining seminar text mining seminar
A x x
B x

C x x x
D
x

  1. Written exam
    • 45 minutes of time
    • 4 tasks (2 computational, 2 theoretical)
    • Literature is not allowed
    • Each student can bring one hand-written A4 sheet of paper and a hand calculator
  2. Data mining seminar
    • Oral presentation of seminar proposals (max 4 minutes per student, use slides template,
      file naming convention DM2009-SurnameFirstname.ppt)
    • Deliver a written report (printed and electronic copy) in Information Society paper format
      on seminar presentations day (use paper template and guidelines)
    • Oral presentation of seminar results (10 minutes for presentation + 5 minutes discussion,
      use slides template and file naming convention DM2009-SurnameFirstname.ppt
  3. Text mining seminar
  4. Data representation and manipulation seminar

Examples of data mining seminars:

  • Janez Bucik (.pdf)
    Microsoft stock quotes dependency analysis
  • Matej Gašperin (.pdf)
    Case study on the use of data minig techniques in food science using honey samples
  • Valentin Koblar (in Slovene .pdf)
    Napoved menjalnega tečaja ameriškega dolarja na podlagi menjalnih tečajev tujih valut

Ideas for seminars

  1. Analyze some data where you are the domain expert, use at least two algorithms
  2. Find some interesting data to analyze, possible sources:

Templates

  • presentation template (.pot)
  • paper template (.doc)
  • paper guidelines (.doc)

Link to last year's web page - Data Mining and Knowledge Discovery 09/10
Last update: 20101208