Journal Papers

M. Drole, I. Kononenko. Pairwise saturations in inductive logic programming. Artificial intelligence review, ISSN 0269-2821, 2016, 1-21.

M. Poberžnik, E. Štrumbelj. The effects of air mass transport, seasonality, and meteorology on pollutant levels at the Iskrba regional background station (1996-2014). Atmospheric environment, ISSN 1352-2310, Jun. 2016, vol. 134, 138-146

E. Canhasi, I. Kononenko. Weighted hierarchical archetypal analysis for multi-document summarization. Computer speech & language, ISSN 0885-2308, May 2016, vol. 37, pp. 24-46.

M. Bohanec, M. Kljajić Borštnar, M. Robnik Šikonja. Explaining machine learning models in sales predictions. Expert systems with applications, ISSN 0957-4174.

P. Vračar, E. Štrumbelj, I. Kononenko. Modelling basketball play-by-play data. Expert systems with applications, ISSN 0957-4174, Feb. 2016, vol. 44, pp. 58-66.

M. Robnik Šikonja. Data generators for learning systems based on RBF networks. IEEE transactions on neural networks and learning systems, ISSN 2162-237X, May 2016, vol. 27, no. 5, pp. 926-938.

E. Štrumbelj. A comment on the bias of probabilities derived from betting odds and their use in measuring outcome uncertainty. Journal of sports economics, ISSN 1527-0025, Jan. 2016, vol. 17, no. 1, pp. 12-26.

A. Čufar, A. Mrhar M. Robnik Šikonja. Assessment of surveys for the management of hospital clinical pharmacy services. Artificial intelligence in medicine, vol. 64, iss. 2, p. 147-158, 2015.

M. Klemenc, E. Štrumbelj. Predicting the outcome of head-up tilt test using heart rate variability and baroreflex sensitivity parameters in patients with vasovagal syncope. Clinical autonomic research, p. 1-8, 2015.

P. Vračar, E. Štrumbelj, I. Kononenko. Modelling basketball play-by-play data. Expert systems with applications, p. 1-26, 2015.

U. Ocepek, J. Rugelj, Z. Bosnić. Improving matrix factorization recommendations for examples in cold start. Expert systems with applications, v. 42, n. 19, p. 6784-6794, 2015.

E. Štrumbelj, M. Robnik Šikonja. Predictive power of fantasy sports data for soccer forecasting. International journal of data mining, modelling and management, 7, n.2, p. 154-163, 2015.

F. Erčulj, E. Štrumbelj. Basketball shot types and shot success in different levels of competitive basketball. PloS one, vol. 10, iss. 6, 2015.

Z. Bosnić, J. Demšar, G. Kešpret, P.P. Rodrigues, J. Gama, I. Kononenko. Enhancing data stream predictions with reliability estimators and explanation. Eng. appl. artif. intell., vol. 34, p.p. 178-192, 2014.

E. Canhasi, I Kononenko. Weighted archetypal analysis of the multi-element graph for query-focused multi-document summarization. Expert systems with applications, Feb. 2014, vol. 41, no. 2, pp. 535-543.

E. Canhasi, I. Kononenko. Multi-document summarization via archetypal analysis of the content-graph joint model. Knowledge and information systems, 2014, vol. 41, no. 3, str. 821-842

U. Ocepek, Z. Bosnić, I. Nančovska Šerbec, J. Rugelj. Exploring the relation between learning style models and preferred multimedia types. Computers & Education, Nov. 2013, vol. 69, pp. 343-355.

B. Petelin, I. Kononenko, V. Malačič, M. Kukar: Multi-level association rules and directed graphs for spatial data analysis. Expert syst. appl., 40(12)4957-4970, 2013.

B. Petelin, I. Kononenko, V. Malačič. M. Kukar, Dynamic fuzzy paths and cycles in multi-level directed graphs. Engineering applications of artificial intelligence, 2014, vol. 37, p. 194-206.

Pičulin, Matej, Robnik Šikonja, Marko. Handling numeric attributes with ant colony based classifier for medical decision making. Expert systems with applications, 2014, 41(16):7524-7535

E. Štrumbelj. On determining probability forecasts from betting odds. International journal of forecasting, 2014, vol. 30, no. 4, 934-943.

E. Štrumbelj., F.Erčulj. Analysis of experts` quantitative assessment of adolescent basketball players and the role of anthropometric and physiological attributes. Journal of Human Kinetics, 2014, vol. 42, 267-276.

E. Štrumbelj.. A comment on the bias of  probabilities derived from betting odds and their use in measuring outcome uncertainty. Journal of sports economics, 2014, (in print, available online)

E. Štrumbelj., I. Kononenko. Explaining prediction models and individual predictions with feature contributions. Knowledge and information systems, 2014, vol. 41, no. 3, 647-665.

M. Toplak, R. Močnik, M. Polajnar, Z. Bosnić, L. Carlsson, C. Hasselgren, J. Demšar, S. Boyer, B. Zupan, J. Stalring. Assessment of machine learning reliability methods for quantifying the applicability domain of QSAR regression models. J. chem. inf. mod., vol. 54, no. 2, p.p. 431-441, Feb. 2014.

Z. Bosnić, P. Vračar, M. D. Radović, G. Devedžić, N. D. Filipović, I. Kononenko: Mining data from hemodynamic simulations for generating prediction and explanation models. IEEE trans. inf. technol. biomed., 16(2)248-254, 2012.

E. Štrumbelj, P. Vračar: Simulating a basketball match with a homogeneous Markov model and forecasting the outcome. Int. j. forecast., 28(2)532-542, 2012.

E. Štrumbelj, I. Kononenko: An efficient explanation of individual classifications using game theory. J. Mach. Learn. Res., 11[1]:1-18, 2010.

Z. Bosnić, I. Kononenko: Automatic selection of reliability estimates for individual regression predictions. Knowl. eng. rev., , 25(1)27-47, 2010.

E. Štrumbelj, Z. Bosnić, I. Kononenko, B. Zakotnik, C. Grašič-Kuhar: Explanation and reliability of prediction models: the case of breast cancer recurrence. Knowledge and information systems, 24(2)305-324, 2010.

M. Robnik-Šikonja, I. Kononenko. Theoretical and Empirical Analysis of ReliefF and RReliefF, Machine Learning Journal, 53: 23-69, 2003.

I. Kononenko: Machine learning for medical diagnosis: History, state of the art and perspective, Invited paper, Artificial Intelligence in Medicine – ISSN 0933-3657, 23(1):89–109, 2001.



I. Kononenko, M.Kukar: Machine Learning and Data Mining: Introduction to Principles and Algorithms, Horwood publ., 2007, XIX, 454 pages.


SICRIS Bibliography of the LKM group