prof. dr. Igor Kononenko

Igor Kononenko je doktoriral leta  1990 iz računalništva in informatike na Univerzi v Ljubljani. Je redni porofesor na Fakulteti za računalništvo in informatiko v Ljubljani. Je predstojnik Laboratorija za kognitivno modeliranje in predstojnik Katedre za umetno inteligenco na isti fakulteti. Njegova raziskovalna področja so umetna inteligenca, strojno učenje, nevronske mreže in kognitivno modeliranje. Je (so)avtor 210 člankov na teh področjih ter 10 učbenikov. Je član uredniškega odbora revij Applied Intelligence Journal (Kluwer Ac. Publ.) in Informatica Journal, dvakrat je bil predsednik programskega odbora Mednarodne kognitivne konference v Ljubljani. Poleg umetne inteligence ga zanima tudi naravna inteligenca: samozdravljenje, komplementarna medicina, relacija med znanostjo in duhovnostjo in duhovna modrost.

Je soavtor knjige (skupaj z Matjažem Kukarjem) MACHINE LEARNING AND DATA MINING: Introduction to Principles and Algorithms, ki je izšla pri angleški znanstveni založbi Horwood Publishing, ter soavtor knjige (skupaj z Ireno Roglič Kononenko) UČITELJI MODROSTI.

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Izbrane objave


I.Kononenko, M.Kukar (2007) Machine learning and data mining : introduction to principles and algorithms. Chichester: Horwood Publishing, . XIX, 454 pages.
 
PETELIN, Boris, KONONENKO, Igor, MALAČIČ, Vlado, KUKAR, Matjaž. Multi-level association rules and directed graphs for spatial data analysis. Expert systems with applications, 2013, vol. 40, issue 12, str. 4957-4970.
 
CANHASI, Ercan, KONONENKO, Igor. Weighted archetypal analysis of the multi-element graph for query-focused multi-document summarization. Expert systems with applications, Feb. 2014, vol. 41, no. 2, str. 535-543.
 
ŠTRUMBELJ, Erik, KONONENKO, Igor. Explaining prediction models and individual predictions with feature contributions. Knowledge and information systems, 2013, str. 1-19.
 
CANHASI, Ercan, KONONENKO, Igor. Multi-document summarization via Archetypal Analysis of the content-graph joint model. Knowledge and information systems, 2013, str. 1-22.
 
BOSNIĆ, Zoran, VRAČAR, Petar, RADOVIĆ, Miloš D., DEVEDŽIĆ, Goran, FILIPOVIĆ, Nenad D., KONONENKO, Igor. Mining data from hemodynamic simulations for generating prediction and explanation models. IEEE transactions on information technology in biomedicine, Mar. 2012, vol. 16, no. 2, str. 248-254.
 
ŠTRUMBELJ, Erik, KONONENKO, Igor. An efficient explanation of individual classifications using game theory. Journal of machine learning research, ISSN 1532-4435. [Print ed.], Jan. 2010, vol. 11, no. [1], str. 1-18
 
KUKAR, Matjaž, KONONENKO, Igor, GROŠELJ, Ciril. Modern parameterization and explanation techniques in diagnostic decision support system : a case study in diagnostics of coronary artery disease. Artificial intelligence in medicine, Jun. 2011, vol. 52, no. 2, str. 77-90
 
M. Robnik Šikonja,  I.Kononenko (2003) Theoretical and empirical analysis of ReliefF and RReliefF. Machine Learning.  53:23-69.
 
I.Kononenko (2001) Machine learning for medical diagnosis: History, state of the art and perspective, Invited paper, Artificial Intelligence in Medicine - ISSN 0933-3657,    vol. 23, no. 1, pp. 89-109.
 
  ŠTRUMBELJ, Erik, BOSNIĆ, Zoran, KONONENKO, Igor, ZAKOTNIK, Branko, GRAŠIČ-KUHAR, Cvetka. Explanation and reliability of prediction models : the case of breast cancer recurrence. Knowledge and information systems, 2010, vol. 24, no. 2, str. 305-324.
 
BOSNIĆ, Zoran, KONONENKO, Igor. Comparison of approaches for estimating reliability of individual regression predictions. Data & Knowledge Engineering, Dec. 2008, vol. 67, no. 3, str. 504-516.
 
I. Kononenko (1993) Inductive and Bayesian learning in medical diagnosis, Applied Artificial Intelligence, Vol. 7, pp. 317-337.
 
I. Kononenko and I. Bratko (1991) Information based evaluation criterion for classifier's performance, Machine Learning Journal, Vol.6, pp.67-80
 
I. Kononenko (1989) Bayesian Neural Networks, Biological Cybernetics Journal Vol. 61, pp. 361-370.
 
B.Cestnik, I.Kononenko, I.Bratko (1987) ASSISTANT 86: A knowledge elicitation tool for sophisticated users, In: I.Bratko, N.Lavrač (eds.): 'Progress in machine learning', Sigma Press.

Podiplomski študenti

AKTIVNI:
Petar Vračar (modeliranje poteka športnih tekmovanj)
Domen Košir (profiliranje spletnih uporabnikov)
Miha Drole (Induktivno logično programiranje)

ZAKLJUČENI:
Zoran Bosnić (ocenjevanje zanesljivosti posameznih predikcij) doktoriral 2007
Erik Štrumbelj (razlaga posameznih predikcij v klasifikaciji in regresiji) doktoriral 2011
Darko Pevec (ocenjevanje zanesljivosti posameznih predikcij v regresiji) doktoriral 2013
Ercan Canhasi (multidocument summarization)doktoriral 2014
Boris Petelin (rudarjenje prostorskih podatkov) doktoriral 2014

Igor Kononenko

prof. dr. Igor Kononenko

T: +386 1 479 8230
F: +386 1 4264 647