Publications

Below is a curated list of my articles in journals (with links for dowload - ), book chapters and conference/workshop papers. The most complete list of my works, is generated dynamically from the COBISS database. A list of publications with their citations is available through my Google Scholar profile . Finally, a list of my publications in the computer science literature can also be generated from the DBLP database.

2015

Articles in Journals


Aleksovski, D., Kocijan, J., and Džeroski, S. (2015). Ensembles of Fuzzy Linear Model Trees for the Identification of Multi-Output Systems. IEEE Transactions on Fuzzy Systems, 29(1): 1-15. DOI: 10.1109/TFUZZ.2015.2489234

Aleksovski, D., Kocijan, J., and Džeroski, S. (2015). Model-tree ensembles for noise-tolerant system identification. Advanced Engineering Informatics, 29(1): 1-15. DOI: 10.1016/j.aei.2014.07.008

Babič Novak, M., Zalar, P., Ženko, B., Schroers, H., Džeroski, S., and Gunde-Cimerman, N. (2015). Candida and Fusarium species known as opportunistic human pathogens from customer-accessible parts of residential washing machines. Fungal Biology, 119(2-3): 95-113. DOI: 10.1016/j.funbio.2014.10.007

Dimitrovski, I., Kocev, D., Kitanovski, I., Loskovska, S., and Džeroski, S. (2015). Improved medical image modality classification using a combination of visual and textual features. Computerized Medical Imaging and Graphics, 39: 14-26. DOI: 10.1016/j.compmedimag.2014.06.005

Dimitrovski, I., Kocev, D., Loskovska, S., and Džeroski, S. (2015). Improving bag-of-visual-words image retrieval with predictive clustering trees. Information Sciences, pp. 15. DOI: 10.1016/j.ins.2015.05.012

Ikonomovska, E., Gama, J., and Džeroski, S. (2015). Online tree-based ensembles and option trees for regression on evolving data streams. Neurocomputing, 150: 458-470. DOI: 10.1016/j.neucom.2014.04.076

Jančič, S., Zalar, P., Kocev, D., Schroers, H., Džeroski, S., and Gunde-Cimerman, N. (2015). Halophily reloaded: new insights into the extremophilic life-style of Wallemia with the description of Wallemia hederae sp. nov. Fungal Diversity, pp. 22. DOI: 10.1007/s13225-015-0333-x

Kenwright, D. A., Bernjak, A., Draegni T., Dzeroski,S., at al. (2015). The discriminatory value of cardiorespiratory interactions in distinguishing awake from anaesthetised states: a randomised observational study. Anaesthesia, pp. 12. DOI: 10.1111/anae.13208

Kuzmanovski, V., Trajanov, A., Leprince, F., Džeroski, S., and Debeljak, M. (2015). Modeling water outflow from tile-drained agricultural fields. Science of the Total Environment, 505: 390-401. DOI: 10.1016/j.scitotenv.2014.10.009

Panov, P., Soldatova, L., Džeroski, S. (2015). Generic ontology of datatypes. Information Sciences, 7: 35. DOI: 10.1016/j.ins.2015.08.006

Simidjievski, N., Todorovski, L., and Džeroski, S. (2015). Predicting long-term population dynamics with bagging and boosting of process-based models. Expert Systems with Applications, 42(22): 8484-8496. DOI: 10.1016/j.eswa.2015.07.004

Simidjievski, N., Todorovski, L., and Džeroski, S. (2015). Learning ensembles of population dynamics models and their application to modelling aquatic ecosystems. Ecological Modelling, 306: 305-317. DOI: 10.1016/j.ecolmodel.2014.08.019

Tanevski, J., Todorovski, L., Kalaidzidis, Y., and Džeroski, S. (2015). Domain-specific model selection for structural identification of the Rab5-Rab7 dynamics in endocytosis. BMC Systems Biology, 9: 31-1-31-17. DOI: 10.1186/s12918-015-0175-x

Trajanov, A., Kuzmanovski, V., LePrince, F., Real, B., Dutertre, A., Maillet-Mezeray, J., Džeroski, S., Debeljak, M. (2015). Estimating drainage periods for agricultural fields from measured data: data-mining methodology and a case study (La JailliÈRe, France). Irrigation and Drainage, pp. 14. DOI: 10.1002/ird.1933

Conference/Workshop Contributions


Levatić, J., Ceci, M., Kocev, D., and Džeroski, S. (2015). Semi-supervised Learning for Multi-target Regression. Third International Workshop on New Frontiers in Mining Complex Patterns, Revised Selected Papers, LNCS 8983: 3-18.

Levatić, J., Supek, F., and Džeroski, S. (2015). Improving QSAR models by exploiting unlabeled data from public databases of bioactive drug-like molecules. In Proc. Seventh Jožef Stefan International Postgraduate School Students' Conference, pp. 114-123. Ljubljana, Slovenia.

Madjarov, G., Dimitrovski, I., Gjorgjevikj, D., and Džeroski, S. (2015). Evaluation of Different Data-Derived Label Hierarchies in Multi-label Classification. Third International Workshop on New Frontiers in Mining Complex Patterns, Revised Selected Papers, LNCS 8983: 19-37.

Mihelčić, M., Džeroski, S., Lavrač, N., Šmuc, T. (2015). Redescription mining with multi-label Predictive Clustering Trees. In Proc. Fourth International Workshop on New frontiers in Mining Complex Patterns (held at ECML PKDD-2015), pp. 86-97. Porto, Portugal.

Osojnik, A., Panov, P., Džeroski, S. (2015). Tree-based approaches for multi-target regression on data streams. In Proc. Fourth International Workshop on New frontiers in Mining Complex Patterns (held at ECML PKDD-2015), pp. 2-13. Porto, Portugal.

Panov, P., Soldatova, L.N, Džeroski, S. (2015). Representing bioinformatics datatypes using the OntoDT ontology. In Proc. Sixth International Conference on Biomedical Ontology, pp. 109-110. Lisbon, Portugal.

2014

Articles in Journals


Levatić, J., Kocev, D., Debeljak, M., and Džeroski, S. (2014). Community structure models are improved by exploiting taxonomic rank with predictive clustering trees. Ecological Modelling, pp. 11. DOI: 10.1016/j.ecolmodel.2014.10.023

Levatić, J., Kocev, D., and Džeroski, S. (2014). The importance of the label hierarchy in hierarchical multi-label classification. Journal of Intelligent Information Systems, pp. 25. DOI: 10.1007/s10844-014-0347-y

Panov, P., Soldatova, L., and Džeroski, S. (2014). Ontology of core data mining entities. Data Mining and Knowledge Discovery, 28(5/6): 1222-1265. DOI: 10.1007/s10618-014-0363-0

Škerjanec, M., Atanasova, N., Čerepnalkoski, D., Džeroski, S., and Kompare, B. (2014). Development of a knowledge library for automated watershed modeling. Environmental Modelling and Software, 54: 60-72.

Zajc, J., Džeroski, S., Kocev, D., Oren, A., Sonjak, S., Tkavc, R., and Gunde-Cimerman, N. (2014). Chaophilic or chaotolerant fungi: a new category of extremophiles? Frontiers in Microbiology, 5: 708-1-708-15. DOI: 10.3389/fmicb.2014.00708

Conference/Workshop Contributions


Aleksovski, D., Kocijan, J., and Džeroski, S. (2014). Model tree ensembles for the identification of multiple-output systems. In Proc. Fourteenth European Control Conference, pages 750-755. Strasbourg, France.

Levatić, J., Ceci, M., Kocev, D., and Džeroski, S. (2014). Semi-supervised learning for multi-target regression. In Proc. Third International Workshop on New frontiers in Mining Complex Patterns (held at ECML PKDD-2014), pp. 110-123. Nancy, France.

Levatić, J., Kocev, D., and Džeroski, S. (2014). The use of the label hierarchy in hierarchical multi-label classification improves performance. Second International Workshop on New Frontiers in Mining Complex Patterns, Revised Selected Papers, LNCS 8399: 162-177.

Piltaver, R., Luštrek, M., Zupančič, J., Džeroski, S., and Gams, M. (2014). Multi-objective learning of hybrid classifiers. In Proc. Twenty First European Conference on Artificial Intelligence, pp. 717-722. Prague, Czech Republic.

Slavkov, I., Karcheska, J., Kocev, D., Kalajdziski, S., and Džeroski, S. (2014). ReliefF for hierarchical multi-label classification. Second International Workshop on New Frontiers in Mining Complex Patterns, Revised Selected Papers, LNCS 8399: 148-161.

Vidmar, N., Simidjievski, N., and Džeroski, S. (2014). Predictive process-based modeling of aquatic ecosystems. In Seventeenth International Conference on Discovery Science, pp 97-101. Bled, Slovenia.

2013

Articles in Journals


Carotenuto, M., Džeroski, S., Ženko, B., and Slavkov, I. (2013). Neuroblastoma tumorigenesis is regulated through the Nm23-H1/h-Prune C-terminal interaction. Scientific Reports, 3: 1351-1-1351-11. DOI: 10.1038/srep01351

Dimitrovski, I., Kocev, D., Loskovska, S., and Džeroski, S. (2013). Fast and efficient visual codebook construction for multi-label annotation using predictive clustering trees. Pattern Recognition Letters, 38: 38-45. DOI: 10.1016/j.patrec.2013.10.016

Gjorgjevikj, D., Madjarov, G., and Džeroski, S. (2013). Hybrid decision tree architecture utilizing local SVMs for efficient multi-label learning. International Journal of Pattern Recognition and Artificial Intelligence, 27(7): 1351004-1-1351004-38. DOI: 10.1142/S021800141351004X

Kocev, D., and Džeroski, S. (2013). Habitat modeling with single- and multi-target trees and ensembles. Ecological Informatics, 18: 79-92. DOI: 10.1016/j.ecoinf.2013.06.003

Kocev, D., Vens, C., Struyf, J., and Džeroski, S. (2013). Tree ensembles for predicting structured outputs. Pattern Recognition, 46(3): 817-833. DOI: 10.1016/j.patcog.2012.09.023

Levatić, J., Džeroski, S., Supek, F., and Šmuc, T. (2013). Semi-supervised learning for quantitative structure-activity modeling. Informatica, 37(1): 173-179.

Radivojac, P., Panov, P., and Džeroski, S. (2013). A large-scale evaluation of computational protein function prediction. Nature Methods, 10(3): 221-227. DOI: 10.1038/nmeth.2340

Stojanova, D., Ceci, M., Malerba, D., and Džeroski, S. (2013). Using PPI network autocorrelation inhierarchical multi-label classification trees forgene function prediction. BMC Bioinformatics,14: 285-1-285-18. DOI: 10.1186/1471-2105-14-285

Stojanova, D., Ceci, M., Appice, A., Malerba, D., and Džeroski, S. (2013). Dealing with spatial autocorrelation when learning predictive clustering trees. Ecological Informatics, 13: 22-39. DOI: 10.1016/j.ecoinf.2012.10.006

Škraban, J., Džeroski, S., Ženko, B., Mongus, D., Gangl, S., and Rupnik, M. (2013). Gut microbiota patterns associated with colonization of different clostridium difficile ribotypes. PloS One, 8(2): 58005-1-58005-13. DOI: 10.1371/journal.pone.0058005

Škraban, J., Džeroski, S., Ženko, B., Tušar, L., and Rupnik, M. (2013). Changes of poultry faecal microbiota associated with Clostridium difficile colonisation. Veterinary Microbiology, 165(3/4): 416-424. DOI: 10.1016/j.vetmic.2013.04.014

Škunca, N., Bošnjak, M., Kriško, A., Panov, P., Džeroski, S., and Šmuc, T. (2013). Phyletic profiling with cliques of orthologs Is enhanced by signatures of paralogy relationships. PLoS Computational Biology, 9(1): 1002852-1-1002852-14. DOI: 10.1371/journal.pcbi.1002852

Conference/Workshop Contributions


Aleksovski, D., Kocijan, J., and Džeroski, S. (2013). Model tree ensembles for modeling dynamic systems. In Proc. Sixteenth International Conference on Discovery Science, LNCS 8140: 17-32, 2013.

Debeljak, M., Kuzmanovski, V., Leprince, F., Réal, B., Džeroski, S., and Trajanov, A. (2013). Prediction of drainage periods and drainage outflow. In Proc. Second York Conference on Pesticide Bahaviour in Soils, Water and Air, 3 pages. York, UK.

Dimitrovski, I., Kocev, D., Loskovska, S., and Džeroski, S. (2013) Fast and scalable image retrieval using predictive clustering trees. In Proc. Sixteenth International Conference on Discovery Science, LNCS 8140: 33-48, 2013.

Jurca, A., and Džeroski, S. (2013). Length dispersion of shoes labelled with the same size in the UK shoe-size system. In Proc. Eleventh Footwear Biomechanics Symposium, 5(1): 39-41. Natal, Brazil.

Kocev, D., Slavkov, I., and Džeroski, S. (2013). Feature ranking for multi-label classicationusing predictive clustering trees. In Proc. Workshop on Solving Complex Machine Learning Problems with Ensemble Methods (held at ECML-PKDD 2013), pp. 56-68. Prague, Czech Republic.

Kuzmanovski, V., Trajanov, A., Džeroski, S., Réal, B., Leprince, F., and Debeljak, M. (2013). Modelling drainage with machine learning methods. In Proc. Second York Conference on Pesticide Bahaviour in Soils, Water and Air, 2 pages. York, UK.

Kuzmanovski, V., Debeljak, M., and Džeroski, S. Time-window selection for optimal generalization with noise variance reduction in ecological data. In Proc. Fifth Jožef Stefan International Postgraduate School Students' Conference, pp. 148-157. Ljubljana, Slovenia.

Levatić, J., Kocev, D., and Džeroski, S. (2013). The use of the label hierarchy in HMC improves performance: a case study in predicting community structure in ecology. In Proc. Second Workshop on New Frontiers in Mining Complex Patterns (held at ECML-PKDD 2013), pp. 189-201. Prague, Czech Republic.

Levatić, J., Ramšak, Ž., Stare, T., Kocev, D., Gruden, K., and Džeroski, S. Gene function prediction for Solanum tuberosum from time-series gene expression data. In Proc. Fifth Jožef Stefan International Postgraduate School Students' Conference, pp. 158-167. Ljubljana, Slovenia.

Massé, F., Paraschiv-Ionescu, A., Ženko, B., Džeroski, S., and Aminian, K. (2013). Lifestyle evaluation using wearable technologies: opportunities for stroke patients. In Proc. International Conference on Neurorehabilitation, 1: 941-945. Toledo, Spain.

Panov, P., Soldatova, L., and Džeroski, S. (2013). OntoDM-KDD: ontology for representing the knowledge discovery process. In Proc. Sixteenth International Conference on Discovery Science, LNCS 8140: 126-140, 2013.

Simidjievski, N., Todorovski, L., and Džeroski, S. Learning bagged models of dynamic systems. In Proc. Fifth Jožef Stefan International Postgraduate School Students' Conference, pp. 177-188. Ljubljana, Slovenia.

Slavkov, I., Karcheska, J., Kocev, D., Kalajdziski, S., and Džeroski, S. (2013). Extending reliefF for hierarchical multi-label classification. In Proc. Second Workshop on New Frontiers in Mining Complex Patterns (held at ECML-PKDD 2013), pp. 156-167. Prague, Czech Republic.

Stojanova, D., Ceci, M., Malerba, D., and Džeroski, S. (2013). Learning hierarchical multi-label classification trees from network data. In Proc. Sixteenth International Conference on Discovery Science, LNCS 8140: 233-248, 2013.

Škerjanec, M., Čerepnalkoski, D., Džeroski, S., Kompare, B., and Atanasova, N. (2013). Modelling dynamic systems using a hybrid approach. In Proc. Convention on Artificial Intelligence and the Simulation of Behaviour, pp. 35-38. Exeter, UK.

Tanevski, J., Todorovski, L., and Džeroski, S. Automated modeling of Rab5Rab7 conversion in endocytosis. In Proc. Fifth Jožef Stefan International Postgraduate School Students' Conference, pages 209-218. Ljubljana, Slovenia.

Tanevski, J., Todorovski, L., Kalaidzidis, Y., and Džeroski, S. (2013). Inductive process modeling of Rab5-Rab7 conversion in endocytosis. In Proc. Sixteenth International Conference on Discovery Science, LNCS 8140: 265-280, 2013.

2012

Articles in Journals


Aho, T., Ženko, B., Džeroski, S., and Elomaa, T. (2012). Multi-target regression with rule ensembles. Journal of Machine Learning Research, 13: 2367-2407.

Čerepnalkoski, D., Taškova, K., Todorovski, L., Atanasova, N., and Džeroski, S. (2012). The influence of parameter fitting methods on model structure selection in automated modeling of aquatic ecosystems. Ecological Modelling, 245: 136-166.DOI: 10.1016/j.ecolmodel.2012.06.001

Debeljak, M., Trajanov, A., Stojanova, D., Leprince, F., and Džeroski, S. (2012). Using relational decision trees to model out-crossing rates in a multi-field setting. Ecological Modelling, 245: 75-83. DOI: 10.1016/j.ecolmodel.2012.04.015

Dimitrovski, I., Kocev, D., Loskovska, S., and Džeroski, S. (2012). Hierarchical classification of diatom images using ensembles of predictive clustering trees. Ecological Informatics, 7(1): 19-29. DOI: 10.1016/j.ecoinf.2011.09.001

Graef, F., Debeljak, M., and Džeroski, S. (2012). A framework for a European network for a systematic environmental impact assessment of genetically modified organisms (GMO). BioRisk, 7: 73-97. DOI: 10.3897/biorisk.7.1969

Madjarov, G., Gjorgjevikj, D., and Džeroski, S. (2012). Two stage architecture for multi-label learning. Pattern Recognition, 45(3): 1019-1034.DOI: 10.1016/j.patcog.2011.08.011

Madjarov, G., Kocev, D., Gjorgjevikj, D., and Džeroski, S. (2012). An extensive experimental comparison of methods for multi-label learning. Pattern Recognition, 45(9): 3084-3104. DOI: 10.1016/j.patcog.2012.03.004

Stojanova, D., Ceci, M., Appice, A., and Džeroski, S. (2012). Network regression with predictive clustering trees. Data Mining and Knowledge Discovery, 25(2): 378-413.DOI: 10.1007/s10618-012-0278-6

Stojanova, D., Kobler, A., Ogrinc, P., Ženko, B., and Džeroski, S. (2012). Estimating the risk of fire outbreaks in the natural environment. Data Mining and Knowledge Discovery, 24(2): 411-442. DOI: 10.1007/s10618-011-0213-2

Taškova, K., Šilc, J., Atanasova, N., and Džeroski, S. (2012). Parameter estimation in a nonlinear dynamic model of an aquatic ecosystem with meta-heuristic optimization. Ecological Modelling, 226(1): 36-61. DOI: 10.1016/j.ecolmodel.2011.11.029

Book chapters


Džeroski, S., Panov, P., and Ženko, B. (2012). Ensemble methods in Machine learning. In R. A. Meyers, editor. Computational Complexity: Theory, Techniques, and Applications, pages 1781-1789. Springer, New York,NY.

Kutnar, L., Kobler, A., and Džeroski, S. (2012). Forecasting changes in beech forest proportion under changed environmental conditions (In Slovenian). In A. Bončina, editor. Beech Forests in Slovenia: Ecology and Management, pages 259-270. Biotechnical Faculty, University of Ljubljana, Slovenia.

Stojanova, D., Debeljak, M., Ceci, M., Appice, A., Malerba, D., and Džeroski, S. (2012). Dealing with spatial autocorrelation in gene flow modeling. In F. Jordan, and S. E. Jørgensen, editors. Models of the Ecological Hierarchy: From Molecules to the Ecosphere, pages 35-49. Elsevier, Amsterdam.

Conference/Workshop Contributions


Džeroski, S. (2012). Machine learning for systems biosciences. In Proc. Fifteenth International Multi-Conference Information Society, pp. 37-40. Ljubljana, Slovenia.

Kuzmanovski, V., Džeroski, S., and Debeljak, M. (2012). Integration of structured expert knowledge. In Proc. Fourth Jožef Stefan International Postgraduate School Students Conference, pp. 137-143. Ljubljana, Slovenia.

Levatić, J., Džeroski, S., Supek, F., and Šmuc, T. (2012). Semi-supervised learning in diverse quantitative structure-activity modeling problems. In Proc. Fifteenth International Multi-Conference Information Society, pp. 60-63. Ljubljana, Slovenia.

Soldatova, L., Džeroski, S., and Panov, P. (2012). Relation for information entities. In Proc. Fifteenth Annual Bio-Ontologies Meeting, pp 1-4. Long Beach, CA.

Tanevski, J., Simidjievski, N., and Džeroski, S. (2012). Biocircuit design with equation discovery. In Proc. Workshop on Learning and Discovery in Symbolic Systems Biology (held at ECML-PKDD 2012), pp. 2-16. Bristol, UK.

2011

Articles in Journals


Atanasova, N., Džeroski, S., Kompare, B., Todorovski, L., and Gal, G. (2011). Automated discovery of a model for dinoflagellate dynamics. Environmental Modelling & Software, 26(5): 658-668. DOI: 10.1016/j.envsoft.2010.11.003

Cortet, J., Kocev, D., Ducobu, C., Džeroski, S., Debeljak, M., and Schwartz, C. (2011). Using data mining to predict soil quality after application of biosolids in agriculture. Journal of Environmental Quality, 40(6): 1972-1982. DOI: 10.2134/jeq2011.0155

Debeljak, M., Squire, G., Kocev, D., Hawes, C., Young, M., and Džeroski, S. (2011). Analysis of time series data on agroecosystem vegetation using predictive clustering trees. Ecological Modelling, 222(14): 2524-2529. DOI: 10.1016/j.ecolmodel.2010.10.021

Dimitrovski, I., Kocev, D., Loskovska, S., and Džeroski, S. (2011). Hierarchical annotation of medical images. Pattern Recognition, 44(10/11): 2436-2449.

Everaert, G., Boets, P., Lock, K., Džeroski, S., and Goethals, P. (2011). Using classification trees to analyze the impact of exotic species on the ecological assessment of polder lakes in Flanders, Belgium. Ecological Modelling, 222(14): 2202-2212. DOI: 10.1016/j.ecolmodel.2010.08.013

Ikonomovska, E., Gama, J., and Džeroski, S. (2011). Learning model trees from evolving data streams. Data Mining and Knowledge Discovery, 23(1): 128-168. DOI: 10.1007/s10618-010-0201-y

Keller, R., Kocev, D., and Džeroski, S. (2011). Trait-based risk assessment for invasive species: high performance across diverse taxonomic groups, geographic ranges and machine learning/statistical tools. Diversity and Distributions, 17(3): 451-461. DOI: 10.1111/j.1472-4642.2011.00748.x

Kutnar, L., Kobler, A., and Džeroski, S. (2011). What might be the effects of global warming on the beech forests in the future? Les, 63(5): 203-207.

Taškova, K., Korošec, P., Šilc, J., Todorovski, L., and Džeroski, S. (2011). Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis. BMC Systems Biology, 5: 159-1-159-52. DOI: 10.1186/1752-0509-5-159

Book chapters


Debeljak, M., and Džeroski, S. (2011). Decision trees in ecological modelling. In F. Jopp, editor. Modeling Complex Ecological Dynamics: An Introduction into Ecological Modelling for Students, Teachers & Scientists, pages 197-209. Springer, Berlin.

Gregorič, A., Zmazek, B., Džeroski, S., Torkar, D., and Vaupotič, J. (2011). Radon as an earthquake precursor - methods for detecting anomalies. In S. d'Amico, editor. Earthquake Research and Analysis: Statistical Studies, Observations, and Planning, pages 179-196. InTech, Rijeka, Croatia.

Conference/Workshop Contributions


Gjorgjioski, V., Kocev, D., and Džeroski, S. (2011). Comparison of distances for multi-label classification with PCTs. In Proc. Fourteenth International Multi-Conference Information Society, pp. 125-128. Ljubljana, Slovenia.

Ikonomovska, E., Driessens, K., Džeroski, S., and Gama, J. (2011). Adaptive windowing for online learning from multiple inter-related data stream. In Proc. Workshops held at Eleventh IEEE International Conference on Data Mining, pp. 697-704. Vancouver, Canada.

Ikonomovska, E., Gama, J., and Džeroski, S. (2011). Incremental multi-target model trees for data streams. In Proc. Twenty Sixtth Annual ACM Symposium on Applied Computing, pp. 988-993. Taichung, Taiwan.

Ikonomovska, E., Gama, J., Ženko, B., and Džeroski, S. (2011). Speeding up Hoeffding-based regression trees with options. In Proc. Twenty Eighth International Conference on Machine Learning, pp. 537-552. Bellevue, WA.

Pugelj, M., and Džeroski, S. (2011). Predicting structured outputs k-Nearest Neighbours Method. In Proc. Fourteenth International Conference on Discovery Science, LNCS 6926: 262-276.

Stojanova, D., Ceci, M., Appice, A., and Džeroski, S. (2011). Network regression with predictive clustering trees. In Proc. European Conference Machine Learning and Knowledge Discovery in Databases, LNCS 6913: 333-348.

Stojanova, D., Ceci, M., Appice, A., Malerba, D., and Džeroski, S. (2011). Global and local spatial autocorrelation in predictive clustering trees. In Proc. Fourteenth International Conference on Discovery Science, LNCS 6926: 307-322.

2010

Articles in Journals


Kocev, D., Naunovski, A., Mitreski, K., Krstić, S., and Džeroski, S. (2010). Learning habitat models for the diatom community in Lake Prespa. Ecological Modelling, 221(2): 330-337. DOI: 10.1016/j.ecolmodel.2009.09.002

Lovrečić, L., Slavkov, I., Džeroski, S., and Peterlin, B. (2010). ADP-ribosylation factor Guanine nucleotide-exchange factor 2 (ARFGEF2): a new potential biomarker in Huntington's disease. Journal of International Medical Research, 38(5): 1653-1662.

Schietgat, L., Vens, C., Struyf, J., Blockeel, H., Kocev, D., and Džeroski, S. (2010). Predicting gene function using hierarchical multi-label decision tree ensembles. BMC Bioinformatics, 11(2): 1-14.

Slavkov, I., Gjorgjioski, V., Struyf, J., and Džeroski, S. (2010). Finding explained groups of time-course gene expression profiles with predictive clustering trees. Molecular BioSystems, 6(4): 729-740.

Stojanova, D., Panov, P., Gjorgjioski, V., Kobler, A., and Džeroski, S. (2010). Estimating vegetation height and canopy cover from remotely sensed data with machine learning. Ecological Informatics, 5(4): 256-266. DOI: 10.1016/j.ecoinf.2010.03.004

Tanevski, J., Džeroski, S., and Kocarev, L. (2010). Approximate Bayesian parameter inference for dynamical systems in systems biology. Prilozi, Oddelenie za matematičko-tehnički nauki, Section of Mathematical and Technical Sciences, 31 (1/2): 73-98.

Zmazek, B., Džeroski, S., Torkar, D., Vaupotič, J., and Kobal, I. (2010). Identification of radon anomalies in soil gas using decision trees and neural networks. Nukleonika, 55(4): 501-505.

Book chapters


Džeroski, S. (2010). Relational data mining. In O. Z. Maimon, and L. Rokach, editors. Data Mining and Knowledge Discovery Handbook, 2nd edition, pages 887-911. Springer, New York, NY.

Džeroski, S. (2010). Inductive databases and constraint-based data mining: Introduction and overview. In S. Džeroski, and B. Goethals, and P. Panov, editors. Inductive Databases and Constraint-based Data Mining, pages 3-26. Springer, Berlin, Germany.

Džeroski, S., and Todorovski, L. (2010). Modeling the dynamics of biological networks from time course data. In S. Choi, editor. Systems Biology for Signaling Networks, pages 275-294. Springer, New York, NY.

Panov, P., Soldatova, L., and Džeroski, S. (2010). Representing entities in the OntoDM data mining ontology. In S. Džeroski, and, B. Goethals, and P. Panov, editors. Inductive Databases and Constraint-based Data Mining, pages 27-58. Springer, Berlin, Germany.

Slavkov, I., and Džeroski, S. (2010). Analyzing gene expression data with predictive clustering trees. In S. Džeroski, and B. Goethals, and P. Panov, editors. Inductive Databases and Constraint-based Data Mining, pages 389-406. Springer, Berlin, Germany.

Struyf, J., and Džeroski, S. (2010). Constrained predictive clustering. In S. Džeroski, and, B. Goethals, and P. Panov, editors. Inductive Databases and Constraint-based Data Mining, pages 155-175. Springer, Berlin, Germany.

Vens, C., Schietgat, L., Struyf, J., Blockeel, H., Kocev, D., and Džeroski, S. (2010). Predicting gene function using predictive clustering trees. In S. Džeroski, and B. Goethals, and P. Panov, editors. Inductive Databases and Constraint-based Data Mining,, pages 365-387. Springer, Berlin, Germany.

Conference/Workshop Contributions


Dimitrovski, I., Kocev, D., Loskovska, S., and Džeroski, S. (2010). ImageCLEF 2009 medical image annotation task: PCTs for hierarchical multi-label classification. In Proc. Tenth Workshop of the Cross-Language Evaluation, pp. 231-238. Corfu, Greece.

Dimitrovski, I., Kocev, D., Loskovska, S., and Džeroski, S. Detection of visual concepts and annotation of images using ensembles of trees for hierarchical multi-label classification. In Proc. Recognizing Patterns in Signals, Speech, Images and Videos, LNCS 6388: 152-162.

Ikonomovska, E., Gama, J., and Džeroski, S. (2010). Incremental option trees for handling gradual concept drift. In Proc. First International Workshop on Handling Concept Drift in Adaptive Indformation Systems: Importance, Challenges and Solutions (held at ECML-PKDD 2010), pp. 17-27. Barcelona, Spain.

Kocev, D., Ženko, B., Paul, P., Todorovski, L., Kuijl, C., Neefjes, J., and Džeroski, S. (2010). Predictive clustering relates gene annotations to phenotype properties extracted from images. In Proc. Fourth International Workshop on Machine Learning in System Biology, pp. 137-139. Edinburgh, Scotland.

Slavkov, I., Aleksovski, D., Savage, N., Todorovski, L., Walburg, K., Ottenhoff, T., and Džeroski, S. (2010). Discovering groups of gene with coordinated response to M. leprae infection. In Proc. Fourth International Workshop on Machine Learning in System Biology, pp. 163-166. Edinburgh, Scotland.

Slavkov, I., Ženko, B., and Džeroski, S. (2010). Evaluation method for featurer rankings and their aggregations for biomarker discovery. In Proc. Third International Workshop on Machine Learning in Systems Biology, Revised Selected Papers 8: 122-135. Ljubljana, Slovenia.

Taškova, K., Korošec, P., Šilc, J., Todorovski, L., and Džeroski, S. (2010). Parameter estimation in an endocytosis model with bioinspired optimization algorithms. In Proc. Fourth International Conference on Bioinspired Optimization Methods and Their Applications, pp. 67-82. Ljubljana, Slovenia.

Taškova, K., Korošec, P., Šilc, J., Todorovski, L., and Džeroski, S. (2010). Parameter estimation in an endocytosis model. In Proc. Fourth International Workshop on Machine Learning in System Biology, pp. 75-80. Edinburgh, Scotland.

2009

Articles in Journals


Kocev, D., Džeroski, S., White, M., Newell, G., and Griffioen, P. (2009). Using single- and multi-target regression trees and ensembles to model a compound index of vegetation condition. Ecological Modelling, 220(8): 1159-1168.

Messéan, A., and Džeroski, S. (2009). Sustainable introduction of GM crops into european agriculture: a summary report of the FP6 SIGMEA research project. Oleagineux Corps Gras Lipides, 16(1): 37-51.

Trajanov, A., Todorovski, L., Debeljak, M., and Džeroski, S. (2009). Modelling the outcrossing between genetically modified and conventional maize with equation discovery. Ecological Modelling, 220(8): 1063-1072.

Book chapters


Debeljak, M., and Džeroski, S. (2009). Applications of data mining in ecological modelling. In S. E. Jørgensen, and T. S. Chon, and F. Recknagel, editors. Handbook of Ecological Modelling and Informatics, pages 409-424. WIT, Southampton, UK.

Džeroski, S. (2009). Machine learning aplications in habitat suitability modeling. In S. E. Haupt, and A. Pasini, and C. Marzban, editors. Artificial Intelligence Methods in the Environmental Sciences, pages 397-411. Springer, Dordrecht, The Netherlands.

Džeroski, S., Panov, P., and Ženko, B. (2009). Ensemble methods in machine learning. In R. A. Meyers, editor. Encyclopedia of Complexity and Systems Science, 6: 5317-5325. Springer, New York, NY.

Conference/Workshop Contributions


Aho, T., Ženko, B., and Džeroski, S. (2009). Rule ensembles for multi-target regression. In Proc. Ninth IEEE International Conference on Data Mining, pp. 21-30. Miami, Florida.

Aleksovski, D., Kocev, D., and Džeroski, S. (2009). Evaluation of distance measures for hierarchical multi-label classification in functional genomics. In Proc. First International Workshop on Learning from Multi-Label Data (held at ECML-PKDD 2009), pp. 5-15. Bled, Slovenia.

Čerepnalkoski, D., Todorovski, L., Atanasova, N., and Džeroski, S. (2009). Incorporating qualitative equations in process-based models. In Proc. Twenty Third International Workshop on Qualitative Reasoning, pp. 136-141. Ljubljana, Slovenia.

Janža, M., Komac, M., Kobler, A., Stojanova, D., Oštir, K., Marsetič, A., Džeroski, S., and Gosar, A. (2009). Methodology for estimating the height and density of vegetation cover from remotely sensed data and possibilities of its use in geology (In Slovene) In Proc. Ninteenth Meeting of Slovenian Geologists, pp. 58-61. Ljubljana, Slovenia.

Naumoski, A., Kocev, D., Atanasova, N., Mitreski, K., Krstić, S., and Džeroski, S. (2009). Predicting chemical parameters of the water from diatom abudance in lake Prespa and its tributaries. In Proc. Fourth International Symposium on Information Technologies in Environmental Engineering, 2: 264-277. Thessaloniki, Greece.

Panov, P., Soldatova, L., and Džeroski, S. (2009). Towards an ontology of data mining investigation. In Proc. Twelfth International Conference on Discovery Science, LNCS 5808: 257-271.

Panov, P., Soldatova, L., and Džeroski, S. (2009). OntoDM: towards an ontology od data mining investigations. In Proc. Workshop on Third Generation Data Mining: Towards Service-Oriented Knowledge Discovery (held at ECML-PKDD 2009), pp. 114-118. Bled, Slovenia.

Slavkov, I., Ženko, B., and Džeroski, S. (2009). Evaluation method for feature rankings and their aggregations for biomarker discivery. In Proc. Third International Workshop on Machine Learning in Systems Biology, pp. 115-124. Ljubljana, Slovenia.

Trajanov, A., Begg, G., Todorovski, L., and Džeroski, S. (2009). Equation-based models of oilseed rape population dynamics developed from simulation outputs of an individual-based model. In Proc. Twelfth International Multi-Conference Information Society, pp. 30-33. Ljubljana, Slovenia.

2008

Articles in Journals


Atanasova, N., Todorovski, L., Džeroski, S., and Kompare, B. (2008). Application of automated model discovery from data and expert knowledge to a real-world domain: Lake Glumsø. Ecological Modelling, 212(1/2): 92-98.

Bohanec, M., Messéan, A., Scatasta, S., Angevin, F., Griffiths, B., Krogh, P., Žnidaršič, M., and Džeroski, S. (2008). A qualitative multi-attribute model for economic and ecological assessment of genetically modified crops. Ecological Modelling, 215(1/3): 247-261.

Bridewell, W., Langley, P., Todorovski, L., and Džeroski, S. (2008). Inductive process modeling. Machine Learning, 71(1): 1-32. DOI: 10.1007/s10994-007-5042-6

Debeljak, M., Squire, G., Demšar, D., Young, M., and Džeroski, S. (2008). Relations between the oilseed rape volunteer seedbank, and soil factors, weed functional groups and geographical location in the UK. Ecological Modelling, 212(1/2): 138-146.

Džeroski, S., and Todorovski, L. (2008). Equation discovery for systems biology: finding the structure and dynamics of biological networks from time course data. Current Opinion in Biotechnology, 19(4): 360-368.

Pivard, S., Demšar, D., Lecomte, J., Debeljak, M., and Džeroski, S. (2008). Characterizing the presence of oilseed rape feral populations on field marginsusing machine learning. Ecological Modelling, 212(1/2): 147-154.

Trajanov, A., Vens, C., Colbach, N., Debeljak, M., and Džeroski, S. (2008). The feasibility of co-existence between conventional and genetically modified crops: using machine learning to analyse the output of simulation models. Ecological Modelling, 215(1-3): 262-271. DOI: 10.1016/j.ecolmodel.2008.02.031

Vens, C., Struyf, J., Schietgat, L., Džeroski, S., and Blockeel, H. (2008). Decision trees for hierarchical multi-label classification. Machine Learning, 73(2): 185-214.

Book chapters


Džeroski, S. Data mining. In S. E. Jørgensen, editor. Encyclopedia of Ecology, 2: 821-830. Elsevier, Amsterdam, The Netherlands.

Conference/Workshop Contributions


Aleksovski, D., Erwing, M., and Džeroski, S. (2008). A functional programming approach to distance-based machine learning. In Proc. Eleventh International Multi-Conference Information Society, pp. 161-165. Ljubljana, Slovenia.

Čerepnalkoski, D., Taškova, K., Todorovski, L., and Džeroski, S. Inducing process-based models of dynamic systems from multiple data sets. In Proc. Second International Workshop on the Induction of Process Models (held at ECML-PKDD 2008), pp. 5-12. Antwerp, Belgium.

Dimitrovski, I., Kocev, D., Loskovska, S., and Džeroski, S. (2008). Hierchical annotation of medical images. In Proc. Eleventh International Multi-Conference Information Society, pp. 174-181. Ljubljana, Slovenia.

Džeroski, S., and Todorovski, L. (2008). Equation discovery for systems biology. In Proc. Second International Workshop on Machine Learning in Systems Biology, pp. 17-26. Brussels, Belgium.

Panov, P., Džeroski, S., and Soldatova, L. OntoDM: an ontology of data mining. In Proc. First International Workshop on Data Mining (held at IEEE ICDM 2008), pp. 752-760. Pisa, Italy.

Pečkov, A., Džeroski, S., and Todorovski, L. (2008). A minimal description length scheme for polynomila regression. In Proc. Twelfth Pacific-Asia Conference on Knowledge Discovery and Data Mining, LNCS 5012: 284-295.

Ristevski, B., Loshkovska, S., Džeroski, S., and Slavkov, I. (2008). A comparison of validation indices for evaluation of clustering results of DNA microarray data. In Proc. Second International Conference on Bioinformatics and Biomedical Engineering, pp. 587-591. Shanghai, China.

Ženko, B., and Džeroski, S. (2008). Learning classification rules for multiple target attributes. In Proc. Twelfth Pacific-Asia Conference on Knowledge Discovery and Data Mining, LNCS 5012: 454-465.

2007

Articles in Journals


Debeljak, M., Cortet, J., Demšar, D., Krogh, P., and Džeroski, S. (2007). Hierarchical clasiffication on environmental factors and agricultural practices affecting soil fauna under cropping systems using Bt maize. Pedobiologia, 51(3): 229-238. DOI: 10.1016/j.pedobi.2007.04.009

Kobler, A., Pfeifer, N., Ogrinc, P., Todorovski, L., Oštir, K., and Džeroski, S. (2007). Repetitive interpolation: a robust algorithm for DTM generation from Aerial Laser Scanner Data in forested terrain. Remote Sensing of Environment, 108(1): 9-23.

Scatasta, S., Wesseler, J., Demont, M., Bohanec, M., Džeroski, S., and Žnidaršič, M. (2007). Multi-attribute modelling of economics and ecological impacts of agricultural innovations on cropping systems. Journal of Systemics, Cybernetics and Informatics, 4(2): 52-59.

Taškova, K., Stojanova, D., Bohanec, M., and Džeroski, S. (2007). A qualitative decision-support model for evaluating researchers. Informatica, 31(4): 479-486.

Book chapters


Džeroski, S. (2007). Inductive logic programming in an Nutshell. In L. Getoor, and B. Taskar, editors. Introduction to Statistical Relational Learning, pages 57-92. MIT Press, Cambridge, UK.

Conference/Workshop Contributions


Appice, A., and Džeroski, S. (2007). Stepwise induction of multi-target model trees. In Proc. Eighteenth European Conference on Machine Learning, LNCS 4701: 502-509.

Appice, A., and Džeroski, S. (2007). Inducing multi-target model trees in a stepwise fashion. In Proc. Fifteenth Italian Symposium on Advanced Database Systems, pp. 16-27. Bari, Italy.

Čerepnalkoski, D., Džeroski, S., Taškova, K., and Todorovski, L. (2007). Learning generic models of dynamic systems. In Proc. Tenth International Multi-Conference Information Society, pp. 186-189. Ljubljana, Slovenia.

Džeroski, S. (2007). Towards a general framework for data mining. In Proc. Fifth International Workshop on Knowledge Discovery in Inductive Databases: Revised, Selected and Invited Papers, LNCS 4747: 259-300.

Džeroski, S., Gjorgjioski, V., Slavkov, I., and Struyf, J. (2007). Analysis of time series data with predictive clustering trees. In Proc. Fifth International Workshop on Knowledge Discovery in Inductive Databases: Revised, Selected and Invited Papers, LNCS 4747: 63-80.

Džeroski, S., Mitreski, K., Krstić, S., and Naumoski, A. Learning habitat models for the diatoms of lake Prespa. In Proc. Eighth National Conference (with international parcipitation) of the Society for Electrotechnics, Telecommunications, Automatics and Informatics, pages 7. Ohrid, Macedonia.

Kobler, A., Ogrinc, P., and Džeroski, S. (2007). Prediction of fire danger in natural environment. In Proc. Slovenian Climate Changes: Impact on Forest and Forestry (Studia Forestalia Slovenica), pp. 457-472. Ljubljana, Slovenia.

Kocev, D., Džeroski, S., White, M., Newell, G., and Griffioen, P. (2007). Ensembles of multi-objective regression trees: a case study for predicting the condition of remnant indigenous vegetation. In Proc. Tenth International Multi-Conference Information Society, pp. 210-213. Ljubljana, Slovenia.

Kocev, D., Struyf, J., and Džeroski, S. (2007). Beam search induction and similarity constraints for predictive clustering trees. In Proc. Fifth International Workshop on Knowledge Discovery in Inductive Databases: Revised, Selected and Invited Papers, LNCS 4747: 134-151.

Kocev, D., Vens, C., Struyf, J., and Džeroski, S. (2007). Ensembles of multi-objective decision trees. In Proc. Eighteenth European Conference on Machine Learning, LNCS 4701: 624-631.

Koppel, E., Slavkov, I., and Džeroski, S. (2007). Knowledge discovery in neuroblastoma-related biological data. In Proc. Second Workshop in Data Mining in Functional Genomics and Proteomics (held at ECML-PKDD 2007), pp. 45-56. Warsaw, Poland.

Panov, P., and Džeroski, S. (2007) Combining bagging and random subspaces to create better ensembles. In Proc. Seventh International Symposium on Intelligent Data Analysis, LNCS 4723: 118-129.

Pečkov, A., Džeroski, S., and Todorovski, L. (2007). Multitarget polynomial regression with constraints. In Proc. International Workshop on Constraint-based Mining and Learning (held at ECML-PKDD 2007), pp. 61-72. Warsaw, Poland.

Stojanova, D., Taškova, K., Bohanec, M., and Džeroski, S. (2007). A qualitative decision-support model for evaluating researchers. In Proc. Tenth International Multi-Conference Information Society, pp. 60-63. Ljubljana, Slovenia.

Struyf, J., and Džeroski, S. (2007). Clustering trees with instant level constraints. In Proc. Eighteenth European Conference on Machine Learning, LNCS 4701: 359-370.

Trajanov, A., Vens, C., Džeroski, S., and Colbach, N. (2007). Studying the presence of genetically modified variants in organic oilseed rape by using relational data mining. In Proc. Twenty First International Conference for Environmental Protection, pp. 417-424. Warsaw, Poland.

2006

Articles in Journals


Atanasova, N., Todorovski, L., Džeroski, S., and Kompare, B. (2006). Constructing a library of domain knowledge for automated modelling of aquatic ecosystems. Ecological Modelling, 194(1-3): 14-36.

Atanasova, N., Todorovski, L., Džeroski, S., Remec-Rekar, Š., Recknagel, F., and Kompare, B. (2006). Automated modelling of a food web in lake Bled using measured data and a library of domain knowledge. Ecological Modelling, 194(1-3): 37-48.

Demšar, D., Džeroski, S., Larsen, T., Struyf, J., Axelsen, J., Bruns-Pedersen, M., and Henning Krogh, P. (2006). Using multi-objective classification to model communities of soil microarthropods. Ecological Modelling, 191: 131-143.

Jeraj, M., Džeroski, S., Todorovski, L., and Debeljak, M. (2006). Application of machine learning methods to paleoecological data. Ecological Modelling, 191: 159-169.

Jurc, M., Perko, M., Džeroski, S., Demšar, D., and Hrašovec, B. (2006). Spruce bark beetles (Ips typographus, Pityogenes chalcographus, Col.: Scolytidae) in the Dinaric mountain forests of Slovenia: monitoring and modeling. Ecological Modelling, 194(1-3): 219-226.

Kobal Grum, D., Kobal, A., Arnerić, N., Horvat, M., Ženko, B., Džeroski, S., and Osredkar, J. (2006). Personality Traits in Miners with Past Occupational Elemental Mercury Exposure. Environmental Health Perspectives, 114(2):290-296.

Kobler, A., Džeroski, S., and Keramitsoglou, I. Habitat mapping using machine learning-extended kernel-based reclassification of an Ikonos satelite image. Ecological Modelling, 191(1): 83-95.

Slavkov, I., Džeroski, S., Peterlin, B., and Lovrečić, L. (2006). Analysis of Huntington's disease gene expression profiles using constrained clustering. Informatica Medica Slovenica, 11(2): 43-51.

Todorovski, L., and Džeroski, S. (2006). Integrated knowledge-driven and data-driven approaches to modeling. Ecological Modelling, 194: 3-13.

Van Assche, A., Vens, C., Blockeel, H., and Džeroski, S. (2006). First order random forest: learning relational classifiers with complex aggregates. Machine Learning, 64(1-3): 149-182.

Zmazek, B., Todorovski, L., Živčić, M., Džeroski, S., Vaupotič, J., and Kobal, I. (2006). Radon in a thermal spring: identification of anomalies related to seismic activity. Applied Radiation and Isotopes, 64: 725-734.

Žnidaršič, M., Jakulin, A., Džeroski, S., and Campichler, C. (2006). Automatic construction of concept hierarchies: the case of foliage-dwelliung spiders. Ecological Modelling, 191: 144-158.

Book chapters


Atanasova, N., Recknagel, F., Todorovski, L., Džeroski, S., and Kompare, B. (2006). Computational Assemblage of Ordinary Differential Equations for Chlorophyll-a Using a Lake Process Equation Library and Measured Data of Lake Kasumigaura. In F. Recknagel, editor. Ecological Informatics: Scope, Techniques, and Applications, pages 409-427. Springer, Berlin, Germany.

Džeroski, S. (2006). Knowledge discovery and data mining. In: Encyclopedia of Artificial Intelligence, pages 648-658. The Japanese Society for Artificial Intelligence.

Conference/Workshop Contributions


Atanasova, N., Mieleitner, J., Džeroski, S., Todorovski, L., and Kompare, B. (2006). Construction of lake Greifensee conceptual model combining machine learning and expert knowledge. In Proc. International Conference on Ecological Modelling, pp. 262-263. Yamaguchi, Japan.

Blockeel, H., Schietgat, L., Struyf, J., Džeroski, S., and Clare, A. (2006). Decision trees for hierarchiral multilabel classsification: a case study in functional genomics. In Proc. Tenth European Conference on Knowledge Discovery in Databases, LNCS pp. 18-29.

Bohanec, M., Messéan, A., Scatasta, S., Angevin, F., Žnidaršič, M., and Džeroski, S. (2006). A qualitative multi-attribute model for economic and ecological assessment of genetically modified crops. In Proc. International Conference on Ecological Modelling, pp. 132-133. Yamaguchi, Japan.

Demšar, D., Džeroski, S., Debeljak, M., and Krogh, P. (2006). Predicting aggregate properties of soil communities vs. comunity structure in an agricultural setting. In Proc. Twentieth International Conference on Informatics for Environmental Protection, pp. 295-302. Aachen, Germany.

Džeroski, S., Erjavec, T., Ledinek, N., Pajas, P., Žabokrtský, Z., and Žele, A. (2006). Towards a Slovene dependency treebank. In Proc. Fifth International Conference on Language Resources and Evaluation, pp. 1388-1391. Genoa, Italy.

Džeroski, S., Kobler, A., Gjorgjioski, V., and Panov, P. (2006). Using decision trees to predict forest stand height and canopy cover from LANSAT and LIDAR data. In Proc. Twentieth International Conference on Informatics for Environmental Protection, pp. 125-133. Aachen, Germany.

Džeroski, S., Trajanov, A., Colbach, N., and Debeljak, M. (2006). Studying the feasibility of co-existence of GM/non-GM crops by analysing the output of simulation models with machine learning. In Proc. International Conference on Ecological Modelling,, pp. 260-261. Yamaguchi, Japan.

Džeroski, S., Slavkov, I., Gjorgjioski, V., and Struyf, J. (2006). Analysis of time series data with predictive clustering trees. In Proc. Fifth International Workshop on Knowledge Discovery in Inductive Database (held at ECML-PKDD 2006), pp. 47-58. Berlin, Germany.

Kobler, A., Džeroski, S., and Fajfar, D. (2006). Predicting fire riskin the natural environment in a geographical information system (in Slovenian). In Ninth International Multi-Conference Information Systems, pp. 35-38. Ljubljana, 2006.

Kobler, A., Pfeifer, N., Ogrinc, P., Todorovski, L., Oštir, K., and Džeroski, S. (2006). Using redundancy in aerial lidar point cloud to generate DTM in steep forestedrelief. In Proc. International Workshop on 3D Remote Sensing in Forestry, pp. 275-280. Vienna, Austria.

Kocev, D., Džeroski, S., and Struyf, J. (2006). Similarity constraints in beam-search induction of predictive clustering trees. In Ninth International Multi-Conference Information Systems, pp. 267-270. Ljubljana, Slovenia.

Mielikäinen, T., Panov, P., and Džeroski, S. (2006). Itemset support queries using frequent itemsets and their condensed representations. In Proc. Ninth International Conference on Discovery Science, LNCS 4265: 161-172.

Pečkov, A., Todorovski, L., and Džeroski, S. (2006). Proper versus ad-hoc MDL principle for polynomial regresion. In Ninth International Multi-Conference Information Systems, pp. 263-266. Ljubljana, Slovenia.

Slavkov, I., Pensa, R., and Džeroski, S. (2006). Using bi-sets that characterize bi-partitions as features for classification: an application for microarray data analysis. In Ninth International Multi-Conference Information Systems, pp. 60-63. Ljubljana, Slovenia.

Stojanova, D., Panov, P., Kobler, A., Džeroski, S., and Taškova, K. (2006). Learning to predict forest fires with different data mining techniques. In Ninth International Multi-Conference Information Systems, pp. 255-258. Ljubljana, Slovenia.

Struyf, J., and Džeroski, S. (2006). Constraint based induction of multi-objective regression trees. In Proc. Fourth International Workshop on Knowledge Discovery in Inductive Databases: Revised, Selected and Invited Papers, LNCS 3933: 222-233.

Taškova, K., Panov, P., Kobler, A., Džeroski, S., and Stojanova, D. (2006). Predicting forest stand properties from satellite images with different data mining techniques. In Ninth International Multi-Conference Information Systems, pp. 259-262. Ljubljana, Slovenia.

Trajanov, A., Panov, P., Colbach, N., Debeljak, M., Džeroski, S., and Messéan, A. (2006). Using simulation models and data mining to study co-existence of Gm/Non-GM crops at regional level. In Proc. Twentieth International Conference on Informatics for Environmental Protection, pp. 493-500. Aachen, Germany.

Trajanov, A., Vens, C., Džeroski, S., and Otero, R. (2006). Using ILP study the presence of genetically modified variants in organic oilseed rape. In Proc. Sixteenth International Conference on Inductive Logic Programming, pp. 107-109. Coruna, Spain.

Trajanov, A., Zdravkova, K., Erjavec, T., and Džeroski, S. (2006). Learning rules for morphological analysis and synthesis of Macedonian nouns, adjectives and verbs. In Proc. Ninth International Multi-Conference Information Society: Language Technologies, pp. 140-145. Ljubljana, Slovenia.

Verdev, M., Bohanec, M., and Džeroski, S. (2006). Decision support for a waste electrical and electronic equipment treatment system. In Ninth International Multi-Conference Information Systems, pp. 93-96. Ljubljana, Slovenia.

Ženko, B., Džeroski, S., and Struyf, J. (2006). Learning predictive clustering rules. In Proc. Fourth International Workshop on Knowledge Discovery in Inductive Databases: Revised, Selected and Invited Papers, LNCS 3933: 234-250.

2005

Articles in Journals


Demšar, D., Džeroski, S., Henning Krogh, P., and Larsen, T. (2005). Using machine learning to predict the impact of agricultural factors on communities of soil microarthropods. Advances in Metodology and Statistics, 2(1): 147-159.

Osredkar, J., Ženko, B., Kobal Grum, D., Krsnik, M., Džeroski, S., Horvat, M., and Kobal, A. (2005). Analysis of the relationship between pineal hormone melatonin level and occupational mercury exposure in ex-miners with machine learning methods. Advances in Metodology and Statistics, 1: 161-172.

Zmazek, B., Živčić, M., Todorovski, L., Džeroski, S., Vaupotič, J., and Kobal, I. (2005). Radon in soil gas: how to identify anomalies caused by earthquakes. Applied Geochemistry, 20: 1106-1119.

Book chapters


Džeroski, S. (2005). Relation data mining. In O. Z. Maimon, and L. Rokach, editors. Data Mining and Knowledge Discovery Handbook, pages 869-897. Springer, New York, NY.

Conference/Workshop Contributions


Atanasova, N., Mieleitner, J., Džeroski, S., Todorovski, L., and Kompare, B. (2005). Development of a lake model using data and expert knowledge - case study: Greifensee. In Proc. Eighth International Multi-Conference Information Society, pp. 216-219. Ljubljana, Slovenia.

Atanasova, N., Todorovski, L., Džeroski, S., and Kompare, B. (2005). Discovering a model of phytoplankton change in lake Glumso from data and expert knowledge. In Proc. Fifth European Conference on Ecological Modelling, pp. 21-22. Pushchino, Russia.

Bohanec, M., Messéan, A., Scatasta, S., Džeroski, S., and Žnidaršič, M. (2005). A qualitative multi-attibute model for economic and ecological evaluation of genetically modified crops. In Proc. Ninteenth International Conference on Informatics for Environmental Protection, pp. 661-668. Brno, Czech Republic.

Debeljak, M., Cortet, J., Demšar, D., and Džeroski, S. (2005). Using data mining to assess the effects of Bt maize on soil microarthropods. In Proc. Ninteenth International Conference on Informatics for Environmental Protection, pp. 615-620. Brno, Czech Republic.

Debeljak, M., Demšar, D., Džeroski, S., Schiemann, J., Wilhelm, R., and Meier-Bethke, S. (2005). Modelling outcrossig of transgenes in maize between neighboring maize fields. In Proc. Ninteenth International Conference on Informatics for Environmental Protection, pp. 610-614. Brno, Czech Republic.

Debeljak, M., Squire, G., Demšar, D., Džeroski, S. (2005). Modelling soil seedbankof oilseed rape arable sites in UK. In Proc. Fifth European Conference on Ecological Modelling, pp. 50-51. Pushchino, Russia.

Driessens, K., and Džeroski, S. (2005). Combining model-based and instance-based learning for first order regression. In Proc. Twenty-Second International Conference on Machine Learning, pp. 193-200. Bonn, Germany.

Džeroski, S., Colbach, N., and Messéan, A. (2005). Analysing the effect of field character on gene flow between oilseed rape varieties and volunteers with regression trees. In Proc. Second International Conference on Co-existence Between GM and non-GM Based Agricultural Supply Chains, pp. 207-211. Montpellier, France.

Kocev, D., Džeroski, S., Struyf, J., and Loskovska, S. (2005). Inductive querying environment for predictive clustering trees. In Proc. Second Balcan Conference on Informatics, pp. 193-199. Skopje, Macedonia.

Lavrač, N., Železný, F., and Džeroski, S. (2005). Local patterns: theory and practice of constraint-based relational subgroup discovery. In Proc. Dagstuhl Seminar on Local Pattern Detection, LNCS 3539: 71-88.

Panov, P., Džeroski, S., Blockeel, H., and Loskovska, S. (2005). Predictive data mining using itemset frequencies. In Proc. Eighth International Multi-Conference Information Society, pp. 224-227. Ljubljana, Slovenia.

Pečkov, A., Džeroski, S., Todorovski, L., and Ljubič, P. (2005). Improving the heuristic solver for polymonial equations - CIPER. In Proc. Second Balcan Conference on Informatics, pp. 397-404. Skopje, Macedonia.

Pivard, S., Lecomte, J., Debeljak, M., Demšar, D., Džeroski, S. (2005). Characterizing oilseed rape feral populations presence using data mining and GIS. In Proc. Fifth European Conference on Ecological Modelling, pp. 154-155. Pushchino, Russia.

Scatasta, S., Wesseler, J., Demont, M., Bohanec, M., Džeroski, S., and Žnidaršič, M. (2005). Multi-attribute modelling of economic and ecological impacts of agricultural innovations on cropping systems. In Proc. Ninth World Multi-Conference on Systemics, Cybernetics and Informatics, pp. 447-452. Orlando, FL.

Slavkov, I., Džeroski, S., Peterlin, B., and Lovrecic, L. (2005). Analysis of Huntington's disease gene expression profiles using constrained clustering. In Proc. First Meeting of Slovenian Bioinformaticians, pp. 62-63. Ljubljana, Slovenia.

Slavkov, I., Džeroski, S., Struyf, J., and Loskovska, S. (2005). Constrained clustering of gene expression profiles. In Proc. Eighth International Multi-Conference Information Society, pp. 212-215. Ljubljana, Slovenia.

Struyf, J., and Džeroski, S. (2005). Constraint based induction of multi-objective regression trees. In Proc. Fourth International Workshop on Knowledge Discovery in Inductive Database (held at ECML-PKDD 2005), 12 pages. Porto, Portugal.

Struyf, J., Džeroski, S., Blockeel, H., and Clare, A. (2005). Hierarchical multi-classification with predictive clustering trees in functional genomics. In Proc. Twelfth Portuguese Conference of Artificial Intelligence, pp. 272-283. Covilha, Portugal.

Struyf, J., Vens, C., Croonenborghs, T., Džeroski, S., and Blockel, H. (2005). Applying predictive clustering trees to the inductive logic programming 2005 challenge data. In Proc. Fifteenth International Conference on Inductive Logic Programming, pp. 111-116. Bonn, Germany.

Struyf, J., Vens, C., Džeroski, S., and Blockeel, H. (2005). Predicting gene function with inductive logic programming and predictive clustering trees (In Slovenian). In Proc. First Meeting of Slovenian Bioinformaticians, pp. 27-30. Ljubljana, Slovenia.

Trajanov, A., Zdravkova, K., Džeroski, S., and Erjavec, T. (2005). Learning rules for morphological analysis and synthesis of Macedonian nouns. In Eighth International Multi-Conference Information Society, pp. 195-198. Ljubljana, Slovenia.

Vojnovski, V., Džeroski, S., and Erjavec, T. (2005). Learning PoS tagging from a tagged Macedonian text corpus. In Proc. Eighth International Multi-Conference Information Society, pp. 199-202. Ljubljana, Slovenia.

Ženko, B., Džeroski, S., and Struyf, J. (2005). Learning predictive clustering rules. In Proc. Fourth International Workshop on Knowledge Discovery in Inductive Database (held at ECML-PKDD 2005), 12 pages. Porto, Portugal.

2004

Articles in Journals


Bohanec, M., Džeroski, S., Žnidaršič, M., Messéan, A., Scatasta, S., and Wesseler, J. (2004). Multi-attribute modelling of economic and ecological impacts of cropping systems. Informatica, 28(4): 387-392.

Blockeel, H., Džeroski, S., Kompare, B., Kramer, S., Pfahringer, B., and Van Laer, W. (2004). Experiments in predicting biodegradability. Applied Artificial Intelligence, 18: 157-181.

Driessens, K., and Džeroski, S. (2004). Integrating guidance into relational reinforcement learning. Machine Learning, 57: 271-304.

Džeroski, S., and Ženko, B. (2004). Is combining classifiers with stacking better than selecting the best one? Machine Learning, 54: 255-273.

Erjavec, T., and Džeroski, S. (2004). Machine learning of morphosyntactic structure: lemmatizing unknown Slovene words. Applied Artificial Intelligence, 18: 17-41.

Kobal Grum, D., Arnerić, N., Kobal, A., Horvat, M., Ženko, B., Džeroski, S., and Osredkar, J. (2004). Emotions and personality traits in former mercury miners. Horizons of Psychology, 13(4): 9-31.

Ogris, N., Džeroski, S., and Jurc, M. (2004). Windthrow factors - a case study on Pokljuka, Forestry and Wood Science and Technology, 74: 59-76.

Todorovski, L., Džeroski, S., and Ljubič, P. (2004). Discovery of polynomial equations for regression. Advances in Metodology and Statistics, 1: 131-142.

Zmazek, B., Živčić, M., Todorovski, L., Džeroski, S., Vaupotič, J., and Kobal, I. (2004). Radon anomalies in soil gas, caused by seismic activity. Acta Geotechnica Slovenica, 1: 12-19.

Conference/Workshop Contributions


Bohanec, M., Džeroski, S., Žnidaršič, M., and Messéan, A. (2004). Multi-attribute modeling of economic and ecological impacts of cropping systems: weed and pest control models. In Proc. Thirtheenth International Electrotechnical and Computer Science Conference, B: 157-160. Slovenian Section IEEE, Ljubljana, Slovenia.

Bohanec, M., Scatasta, S., Džeroski, S., and Žnidaršič, M. (2004). Multi-attribute modeling of economic impacts of cropping systems. In Proc. Seventh International Multi-Conference Information Society, pp. 91-94. Ljubljana, Slovenia.

Demšar, D., Džeroski, S., Krogh, P., and Larsen, T. (2004). Using multiobjective classification to model communities of soil microarthropods. In Proc. Fourth International Workshop on Environmental Applications of Machine Learning, pp. 21-22. Bled, Slovenia.

Demšar, D., Džeroski, S., Krogh, P., and Larsen, T. (2004). Using multiobjective classification to model communities of soil microarthropods. In Proc. Thirthteenth International Electrotechnical and Computer Science Conference, A: 291-294. Slovenian Section IEEE, Ljubljana, Slovenia.

Demšar, D., Džeroski, S., Krogh, P., and Larsen, T. (2004). Discovery the most important factors for communities of soil microarthropods using machine learning. In Proc. International Conference Applied Statistics, pp. 17-20. Ljubljana, Slovenia.

Demšar, D., Džeroski, S., Krogh, P., and Larsen, T. (2004). Discovering the most important factors for communities of soil microarthropods using machine learning. In Proc. Eighteenth International Conference on Informatics for Environmental Protection, pp. 194-204. Geneve, Switzerland.

Džeroski, S., Ljubič, P., and Todorovski, L. (2004). Towards inductive databases for modeling quantitative structure-activity relationships. In Proc. Seventh Workshop on Mining Scientific and Engineering Datasets, pp. 53-59. Lake Buena Vista, FL.

Džeroski, S., Todorovski, L., and Ljubič, P. Inductive databases of polynomial equations. In Proc. Sixth International Conference on Data Warehousing and Knowledge Discovery, LNCS 3181: 157-168.

Jurc, M., Perko, M., Džeroski, S., Demšar, D., and Hrašovec, B. (2004). Modeling two spruce bark beetle populations (Scolytidae: Ips typographus, Pityogenes chalcographus) in Southwestern Slovenia: a tool in the management of economically important species. In Proc. Fourth European Conference on Ecological Modelling, pp. 69-70. Bled, Slovenia.

Kobal, A., Sešek-Briški, A., Krsnik, M., Horvat, M., Dizdarevič, T., Ženko, B., Džeroski, S., Arnerić, N., and Osredkar, J. (2004). Potential kidney effects in ex-mines of the Idrija mercury mine exposed to elemental mercury and silica dust. In Proc. Seventh International Conference on Mercury as a Global Pollutant, 1: 447-451. Ljubljana, Slovenia.

Kobal, A., Ženko, B., Kobal Grum, D., Krsnik, M., Džeroski, S., Horvat, M., and Osredkar, J. (2004). Analysis of excretion of pineal gland hormone melatonin in ex-mercury miners with learning methods. In Proc. International Conference Applied Statistics, pp. 32-36. Ljubljana, Slovenia.

Kobal Grum, D., Arnerić, N., Kobal, A., Horvat, M., Ženko, B., Džeroski, S., and Osredkar, J. Can occupational exposure to elementary mercury increased the risk of suicide? In Proc. Seventh International Conference on Mercury as a Global Pollutant, 1: 452-457. Ljubljana, Slovenia.

Popit, A., Todorovski, L., Zmazek, B., Vaupotič, J., Džeroski, S., and Kobal, I. (2004). Analysis of radon concentration in Slovenian thermal waters for earthquake prediction. In Proc. Fourth International Workshop on Environmental Applications of Machine Learning, pp. 53-54. Bled, Slovenia.

Todorovski, L., and Džeroski, S. (2004). Knowledge-based framework for modeling dynamic environmental systems. In Proc. Fourth European Conference on Ecological Modelling, pp. 121-122. Bled, Slovenia.

Todorovski, L., and Džeroski, S. (2004). Integrating knowledge-driven and data-driven approaches to modeling. In Proc. Eighteenth International Conference on Informatics for Environmental Protection, pp. 215-226. Geneve, Switzerland.

Todorovski, L., Ljubič, P., and Džeroski, S. (2004). Inductive polynomial equations for regression. In Proc. Fifteenth European Conference on Machine Lerning, LNCS 3201: 441-452. Pisa, Italy. DOI: 10.1007/978-3-540-30115-8_41

Vens, C., Van Assche, A., Blockeel, H., and Džeroski, S. (2004). First order random forests with complex aggregates. In Proc. Fourteenth International Conference on Inductive Logic Programming, LNCS 3194: 323-340. Porto, Portugal.

Ženko, B., Džeroski, S., Kobal, A., Kobal Grum, D., Arnerić, N., Osredkar, J., and Horvat, M. (2004). Relating personality traits and mercury exposure in miners with machine learning methods. In Proc. Eighteenth International Conference on Informatics for Environmental Protection, pp. 400-412. Geneva, Switzerland.

2003

Articles in Journals


Džeroski, S. (2003). Multi-relational data mining: an introduction. SIGKDD Explorations, 5: 1-16.

Džeroski, S., and Drumm, D. (2003). Using regression trees to identify the habitat preference of the sea cucumber (Holothuria leucospilota) on Rarotonga, Cook Island. Ecological Modelling, 170: 219-226.

Džeroski, S., and Todorovski, L. (2003). Learning population dynamics models from data and domain knowledge. Ecological Modelling, 170: 129-140.

Jerina, K., Debeljak, M., Džeroski, S., Kobler, A., and Adamič, M. (2003). Modeling the brown bear population in Slovenia: a tool in the conservation management of a threatened species. Ecological Modelling, 170 (2/3): 453-469.

Todorovski, L., and Džeroski, S. (2003). Combining classifiers with meta decision trees. Machine learning, 50: 223-249.

Todorovski, L., Džeroski, S., Langley, P., and Potter, C. (2003). Using equation discovery to reverse an Earth ecosystem model of the carbon netproduction. Ecological Modelling, 170: 141-154.

Zmazek, B., Todorovski, L., Džeroski, S., Vaupotič, J., and Kobal, I. (2003). Application of decision trees to the analysis of soil radon data for earthquake prediction. Applied Radiation and Isotopes, 58: 697-706.

Book chapters


Džeroski, S. (2003). Relational reinforcement learning for agents in worlds with objects. In E. Alonso, D. Kudenko, and D. Kazakov, editors. Adaptive Agents and Multi-Agent Systems, LNCS 2636: 306-321. Springer, Heidelberg, Germany.

Conference/Workshop Contributions


Demšar, D., Džeroski, S., Larsen, T., and Krogh, P. (2003). Identifying the most important agricultural factors for the soil community of microathropods. In Proc. Twelfth International Electrotechnical and Computer Science Conference, pp. 369-372. Slovenian Section IEEE, Ljubljana, Slovenia.

Džeroski, S., Todorovski, L., and Ljubič, P. (2003). Using constraints in discovery dynamics. In Proc. Sixth International Conference on Discovery science, LNCS 2834: 297-305.

Džeroski, S., Todorovski, L., and Ljubič, P. Inductive databases of polynomial equations. In Proc. Second International Workshop on Knowledge Discovery in Inductive Databases, pp. 28-43. Zagreb, Croatia.

Džeroski, S., Todorovski, L., Zmazek, B., Vaupotič, J., and Kobal, I. (2003). Modelling soil radon concentration for eartquake prediction. In Proc. Sixth International Conference on Discovery Science, LNCS 2834: 87-99.

Džeroski, S., Todorovski, L., Zmazek, B., Vaupotič, J., and Kobal, I. (2003). Modelling soil radon concentration for eartquake prediction. In Proc. Workshop on Mining Scientific and Engineering Databasets, pp. 19-28. San Francisco, CA.

Erjavec, T., and Džeroski, S. (2003). Lemmatising unknown words in highly inflective languages. In Proc. International Workshop Information Extraction for Slavonic and Other Central and Eastern European Languages, pp. 70-76. Sofia, Bolgaria.

Todorovski, L., and Džeroski, S. (2003). Using domain specific knowledge for automated modeling. In Proc. Fifth International Conference on Intelligent Data Analysis, LNCS 2810: 48-59.

Todorovski, L., and Džeroski, S. (2003). Revision of equation-based models. In Proc. Workshop on Mining Scientific and Engineering Databasets, pp. 79-88. San Francisco, CA.

Todorovski, L., Džeroski, S., and Ljubič, P. (2003). Discovery of polynomial equations for regression. In Proc. Sixth International Multi-Conference Information Society, A: 151-154. Ljubljana, Slovenia.

Železný, F., Lavrač, N., and Džeroski, S. (2003). Contraint-based relational subgroup discovery. In Proc. Second International Workshop on Multi-Relational Data Mining (held at KDD 2003), pp. 135-150. Washington, DC.

Ženko, B., and Džeroski, S. Kombiniranje klasifikatorjev s skladanjem. In Proc. Twelfth International Electrotechnical and Computer Science Conference, pp. 467-470. Slovenian Section IEEE, Ljubljana, Slovenia.

Ženko, B., Džeroski, S., Kobal, A., Kobal Grum, D., Arnerić, N., Osredkar, J., and Horvat, M. (2003). Relating personality traits and mercury exposure in miners with machine learning methods: a preliminary study. In Proc. Sixth International Multi-Conference Information Society, A: 163-166. Ljubljana, Slovenia.

2002

Articles in Journals


Ženko, B., and Džeroski, S. (2002). Predicting biodegradability with regression trees (In Slovene). Electrotechnical Review, 69(1): 60-68.

Book chapters


Džeroski, S. (2002). Inductive logic programming approaches. In W. Klösgen, and J. M. Zytkow, editors. Handbook of Data Mining and Knowledge Discovery, pages 348-353. Oxford University Press, Oxford, UK.

Džeroski, S. (2002). Environmental sciences. In W. Klösgen, and J. M. Zytkow, editors. Handbook of Data Mining and Knowledge Discovery, pages 817-830. Oxford University Press, Oxford, UK.

Džeroski, S., and Todorovski, L. (2002). Encoding and using domain knowledge on population dynamics for equation discovery. In L. Magnani, N. J. Nersessian, and C. Pizzi, editors. Logical and Computational Aspects of Model-Based Reasoning, pages 227-247. Kluwer, Dordrecht, The Netherlands.

Conference/Workshop Contributions


Blockeel, H., Bruynooghe, M., Džeroski, S., Ramon, J., and Struyf, J. (2002). Hierarchical multi-classification. In Proc. First Workshop on Multi-Relational Data Mining (held at KDD 2002), pp. 21-35. Edmonton, Canada.

Driessens, K., and Džeroski, S. (2002). On using guidance in relational reinforcement learning. In Proc. Twelfth Belgian-Dutch Conference on Machine Learning, pp. 31-38. Utrecht, The Netherlands.

Driessens, K., and Džeroski, S. (2002). Integrating experimentation and guidance in relational reinforcement learning. In Proc. Nineteenth International Conference on Machine Learning, pp. 115-122. San Francisco, CA

Džeroski, S., Todorovski, L., and Blockeel, H. (2002). Relational ranking with predictive clustering trees. In Proc. Workshop on Active Mining, pp. 9-15. Maebashi, Japan.

Džeroski, S., and Ženko, B. (2002). Stacking with multi-response model trees. In Proc. Third International Workshop on Multiple Classifier System, LNCS 2364: 201-211.

Džeroski, S., and Ženko, B. (2002). Is combining classifiers better than selecting the best one? In Proc. Nineteenth International Conference on Machine Learning, pp. 123-129. San Francisco, CA.

Langley, P., Sanchez, J., Todorovski, L., and Džeroski, S. (2002). Inducing process models from continuous data. In Proc. Nineteenth International Conference on Machine Learning, pp. 347-354. San Francisco, CA.

Todorovski, L., Blockeel, H., and Džeroski, S. (2002). Ranking with predictive clustering trees. In Proc. Thirteenth European Conference on Machine Learning, LNCS 2430: 444-455.

Todorovski, L., Cestnik, B., Kline, M., Lavrač, N., and Džeroski, S. (2002). Qualitative clustering of short time-series: a case study of firms reputation data. In Proc. Second International Workshop on Integration and Collaboration Aspects of Data Mining, Decision Support and Meta-Learning (held at ECML-PKDD 2002), pp. 141-149. Helsinki, Finland.

Todorovski, L., Cestnik, B., Kline, M., Lavrač, N., and Džeroski, S. (2002). Qualitative clustering of short time series: a case study of firms reputation data. In proc. Fifth International Multi-Conference Information Society, pp. 143-146. Ljubljana, Slovenia.

Žabokrtský, Z., Sgall, P., and Džeroski, S. (2002). A machine learning approach to automatic functor assignment in the Prague Dependency Treebank. In Proc. Third International Conference on Language Resources and Evaluation, V: 1513-1520. Las Palmas de Grand Canaria, Spain.

Ženko, B., and Džeroski, S. (2002). Stacking with an extended set of meta-level attributes and MLR. In Proc. Thirteenth European Conference on Machine learning, LNCS 2430: 493-504.

2001

Articles in Journals


Comas, J., Džeroski, S., Gibert, K., R.-Roda, I., and Sanchez-Marre, M. (2001). Knowledge discovery by means of inductive methods in wastewater treatment plant data. AI Communications, 14: 45-62.

Debeljak, M., Džeroski, S., Jerina, K., Kobler, A., and Adamič, M. (2001). Habitat suitability modeling for red deer (Cervus elaphus L.) in South-Western Slovenia with classification trees. Ecological Modelling, 138: 321-330.

Džeroski,S. (2001). Applications of symbolic machine learning to ecological modelling. Ecological Modelling, 146: 263-273.

Džeroski, S., Raedt, L., and Driessens, K. (2001). Relational reinforcement learning. Machine Learning, 43: 7-52.

Džeroski, S., and Žabokrtský, Z. (2001). A machine learning approach to atomatic functor assignment in the Prague Dependency Treebank. Prague Bulletin of Mathematical Linguistics, 76: 35-43.

Kompare, B., Todorovski, L., and Džeroski, S. (2001). Modeling and prediction of phytoplankton growth with equation discovery: case study - Lake Glumsø, Denmark. Verhandlungen - Internationale Vereinigung für Theoretische und Angewandte Limnologie, 27: 3626-3631.

Walley, W., Grbović, J., and Džeroski, S. (2001). A reappraisal of saprobic values and indicator weights based on Slovenian river quality data. Water Research, 35: 4285-4292.

Book chapters


Džeroski, S. (2001). Data mining in a nutshell. In: S. Džeroski, and N. Lavrač, editors. Relational Data Mining, pages 3-27. Springer, Berlin, Germany.

Džeroski, S. (2001). Relational data mining applications: an overview. In: S. Džeroski, and N. Lavrač, editors. Relational Data Mining, pages 339-364. Springer, Berlin, Germany.

Džeroski, S., and Lavrač, N. (2001). An introduction to inductive logic programming. In: S. Džeroski, and N. Lavrač, editors. Relational Data Mining, pages 48-73. Springer, Berlin, Germany.

Todorovski, L., Weber, I., Lavrač, N., Stěpánkova, O., Džeroski, S., Kazakov, D., Zupanič, D., and Flach, P. (2001). Internet resources on ILP for KDD. In: S. Džeroski, and N. Lavrač, editors. Relational Data Mining,, pages 375-388. Springer, Berlin, Germany.

Conference/Workshop Contributions


Džeroski, S., and Grbović, J. (2001). Relating biodiversity of river communities to physical and chemical water properties. In Proc. Fifteenth International Symposium on Informatics for Environmental Protection, 1: 367-372. Metropolis Verlag, Marburg, Germany.

Džeroski, S., Hristovski, D., and Peterlin, B. (2001). Predicting the severity of the clinical phenotype of male infertility for patients with Y-chromosome deletions by using data mining. In Proc. Fourth International Multi-Conference Information Society, pp. 103-147. Ljubljana, Slovenia.

Džeroski, S., and Todorovski, L. (2001). Integrating knowledge-based and data-driven modeling of population dynamics. In Proc. Fifteenth International Symposium on Informatics for Environmental Protection, 2:653-658. Metropolis Verlag, Marburg, Germany.

Hristovski, D., Stare, J., Peterlin, B., and Džeroski, S. (2001). Supporting discovery in medicine by association rule mining in Medline and UMLS. In Proc. Tenth World Congress on Medical Informatics, pp. 1344-1348. IOS Press, Amsterdam, The Netherlands.

Todorovski, L., and Džeroski, S. (2001). Theory revision in equation discovery. In Proc. Fourth International Conference on Discovery science, LNCS 2226: 390-400.

Todorovski, L., and Džeroski, S. (2001). Using domain knowledge on population dynamics modeling for equation discovery. In Proc. Twelfth European Conference on Machine Learning, LNCS 2167: 478-490.

Ženko, B., Todorovski, L., and Džeroski, S. (2001). A comparison of stacking with meta desicion trees to bagging, boosting, and stacking with other methods. In Proc. IEEE International Conference on Data Mining, pp. 669-670. IEEE Computer Society, Los Alamitos, CA.

Ženko, B., Todorovski, L., and Džeroski, S. (2001). A comparison of stacking with meta decision trees to other combining methods. In Proc. Fourth International Multi-Conference Information Society, pp. 144-147. Ljubljana, Slovenia.

Ženko, B., Todorovski, L., and Džeroski, S. (2001). A comparison of stacking with MDTs to bagging, boosting, and other stacking methods. In Proc. Workshop on Integrating aspects of data mining,decision support and meta-learning (held at ECML-PKDD 2001), pp. 163-174. Freiburg, Germany.

2000

Articles in Journals


Džeroski, S., Demšar, D., and Grbović, J. (2000). Predicting chemical parameters of river water quality from bioindicator data. Applied Intelligence, 13(1): 7-17.

Džeroski, S., Hristovski, D., and Peterlin, B. (2000). Using data mining and OLAP to discover patterns in a database of patients with Y-chromosome deletions. JAMIA. Journal of the American Medical Informatics Association, pp. 215-219.

Gamberger, D., Lavrač, N., and Džeroski, S. (2000). Noise detection and elimination in data preprocessing: experiments in medical domains. Applied Artificial Intelligence, 14(2): 205-223.

Kampichler, C., Džeroski, S., and Wieland, R. (2000). Application of machine learning techniques to the analysis of soil ecological data bases: relationships between habitat features and Collembolan community characteristics. Soil Biology and Biochemistry, 32: 197-209.

Book chapters


Džeroski, S., Cussens, J., and Manandhar, S. (2000). An introduction to inductive logic programming and learning language in logic. In J. Cussens, and S. Džeroski, editors. Learning Language in Logic, LNCS 1925: 3-35. Springer, Berlin, Germany.

Džeroski, S., and Erjavec, T. (2000). Learning to lemmatise Slovene words. In J. Cussens, and S. Džeroski, editors. Learning Language in Logic, LNCS 1925: 69-88. Springer, Berlin, Germany.

Conference/Workshop Contributions


Comas, J., Džeroski, S., and Sanchez-Mare, M. (2000). Applying machine learning methods to wastewater treatment plant data. In Proc. Second Workshop on Binding Environmental Science and Artificial Intelligence, pp. 10-1-1-11. Berlin, Germany.

Džeroski, S., Erjavec, T., and Zavrel, J. (2000). Morphosyntactic tagging of Slovene: evaluating taggers and tagsets. In Proc. Second International Conference on Language Resources and Evaluation, II: 1099-1104. National Technical University of Athens, Greece.

Džeroski, S., Hristovski, D., Kunej, T., and Peterlin, B. (2000). A data mining approach to the development of a diagnostic test for male infertility. In Proc. Sixteenth International Congress of the European Federation for Medical Informatics, 77: 779-783. IOS Press, Amsterdam, The Netherlands.

Hristovski, D., Džeroski, S., Peterlin, B., and Rožić, A. (2000). Supporting discovery in medicine by association rule mining of bibliographic databases. In Proc. Fourth European Conference on Principles and Practice of Knowledge Discovery in Databases, LNCS 1910: 446-451.

Kobler, A., Hočevar, M., and Džeroski, S. (2000). Forest border identification by rule-based classification of Landsat TM and GIS data. In Proc. Workshop on machine learning of spatial knowledge (held at ICML-2000), pp. 62-69. Stanford, CA.

Kobler, A., Hočevar, M., and Džeroski, S. (2000). Forest border identification by rule-based classification of landsat TM and GIS data In Proc. Workshop on International Cooperation and Technology Transfer (International Archives of Photogrammetry and Remote Sensing), XXXII(6W8/1): 93-100. RICS Books, London, UK.

Kobler, A., Hočevar, M., and Džeroski, S. (2000). Mapping spontaneous afforestation 1981-1995 in Slovenia by remote sensing and GIS. In Proc. Second International Conference on GIS for Earth Science Applications, 8 pages. Izmir, Turkey.

Todorovski, L., and Džeroski, S. (2000). Combining multiple models with meta decision trees. In Proc. Fourth European Conference on Principles and Practice of Knowledge Discovery in Databases, LNCS 1910: 54-64.

Todorovski, L., and Džeroski, S. (2000). Combining two aspects of meta-learning with heterogeneous meta decision trees. In Proc. Fifth International Workshop on Multistrategy Learning, pp. 221-232. Universidade do Porto, Portugal.

Todorovski, L., Džeroski, S., Srinivasan, A., Whiteley, J., and Gavaghan, J. (2000). Discovering the structure of partial differential equations from example behaviour. In Proc. Seventeenth International Conference on Machine Learning, pp. 991-998. Morgan Kaufman, San Francisco, CA.

Ženko, B., Džeroski, S. (2000). Predicting biodegradability with regression trees. In Proc. Ninth Electrotechnical and Computer Science Conference, B: 275-278. Slovenian Section IEEE, Ljubljana, Slovenia.

1999

Articles in Journals


Debeljak, M., Džeroski, S., and Adamič, M. (1999). Interactions among the red deer (Cervus elaphus, L.) population, meteorological parameters and new growth of the natural regenerated forest in Sneznik, Slovenia. Ecological Modelling, 121: 51-61.

Dimec, J., Džeroski, S., Todorovski, L., and Hristovski, D. (1999). WWW search engine for Slovenian and English medical documents. Studies in Health Technology and Informatics, 68: 547-552.

Lavrač, N., Džeroski, S., and Numao, M. (1999). Inductive logic programming for relational knowledge discovery. New Generation Computing, 17: 3-23.

Book chapters


Džeroski, S., Todorovski, L., Bratko, I., Kompare, B., and Križman, V. (1999). Equation discovery with ecological applicatins. In A. H. Fielding, editor. Machine Learning Methods for Ecological Applications, pages 185-207. Kluwer Academic Publishers, Boston, MA.

Conference/Workshop Contributions


Blockeel, H., Džeroski, S., and Grbović, J. (1999). Simultaneous prediction of multiple chemical parameters of river water quality with TILDE. In Proc. Third European Conference on Principles of Data Mining and Knowledge Discovery, LNCS 1704: 32-40.

Cussens, J., Džeroski, S., and Erjavec, T. (1999). Morphosyntactic tagging of Slovene Using progol. In Proc. Ninth International Conference on Inductive Logic Programming, LNCS 1634: 68-79.

Dimec, J., Todorovski, L., Hristovski, D., and Džeroski, S. (1999). The personalised search engine for Slovenian and English medical documents. In Proc. Twenty-Third Library Systems Seminar on Managing Multimedia Collections, pp. 56-63. National and University Library, Ljubljana, Slovenia.

Džeroski, S., Blockeel, H., Kompare, B., Kramer, S., Pfahringer, B., and Van Laer, W. (1999). Experiments in predicting biodegradability. In Proc. Ninth International Conference on Inductive Logic Programming, LNCS 1634: 80-91.

Križman, V., Gams, M., and Džeroski, S. (1999). Discovering dynamics from data. In Proc. International Multi-Conference Information Society, pp. 119-123. Ljubljana, Slovenia.

Todorovski, L., and Džeroski, S. (1999). Experiments in meta-level learning with ILP. In Proc. Third European Conference on Principles of Data Mining and Knowledge Discovery, LNCS 1704: 98-106.

1998

Articles in Journals


Džeroski, S., and Erjavec, T. (1998). Inductive learning of multilingual morphology. Electrotechnical Review, 65(5): 296-302.

Džeroski, S., Schulze-Kremer, S., Heidtke, K., Siems, K., Wettschereck, D., and Blockeel, H. (1998). Diterpene structure elucidation from [sup]13C NMR spectra with inductive logic programming. Applied Artificial Intelligence, 12: 363-383.

Todorovski, L., Džeroski, S., and Kompare, B. (1998). Modelling and prediction of phytoplankton growth with equation discovery. Ecological Modelling, 113: 71-81.

Zupan, B., and Džeroski, S. (1998). Acquiring background knowledge for machine learning using function decomposition: a case study in rheumatology. Artificial Intelligence in Medicine, 14: 101-117.

Book chapters


Džeroski, S., Grbović, J., and Walley, W. (1998), Machine learning applications in biological classification of river water quality. In R. Michalski, I. Bratko, M. Kubat, editors. Machine Learning, Data Mining and Knowledge Discovery: Methods and Applications, pages 429-448. J. Wiley & Sons, Chichester, UK.

Conference/Workshop Contributions


Dimec, J., Džeroski, S., Todorovski, L., and Hristovski, D. (1998). A search engine for Slovene and English medical documents on the Internet. In Proc. International Multi-Conference Information Society: Language Technologies for the Slovene Language, pp. 43-48. Ljubljana, Slovenia.

Džeroski, S., Raedt, L., and Blockeel, H. (1998). Relational reinforcement learning. In Proc. Eight International Conference on Inductive Logic Programming, LNCS 1446: 11-22.

Džeroski, S., Jacobs, N., Molina, M., and Moure, C. (1998). ILP experiments in detecting traffic problems. In Proc. Tenth European Conference on Machine Learning, LNCS 1398: 61-66.

Manandhar, S., Džeroski, S., and Erjavec, T. (1998). Learning multilingual morphology with CLOG. In: In Proc. Eight International Conference on Inductive Logic Programming, LNCS 1446: 135-144.

1997

Articles in Journals


Džeroski, S., Grbović, J., Walley, W., and Kompare, B. (1997). Using machine learning techniques in the construction of models. 2, Data analysis with rule induction. Ecological Modelling, 95(1): 95-111.

Book chapters


Džeroski, S., Schulze-Kremer, S., Heidtke, K., Siems, K., and Wettschereck, D. (1997). Diterpene structure elucidation from 13[sup]C NMR-spectra with machine learning. In N. Lavrač, E. Keravnou and, B. Zupan, editors. Intelligent Data Analysis in Medicine and Pharmacology, pages 207-225. Kluwer Academic Publishers, Boston, MA.

Lavrač, N., Gamberger, D., and Džeroski, S. (1997). Noise elimination applied to early diagnosis of rheumatic diseases. In N. Lavrač, E. Keravnou, and B. Zupan, editors Intelligent Data Analysis in Medicine and Pharmacology, pages 187-205. Kluwer Academic Publishers, Boston, MA.

Conference/Workshop Contributions


Dimopoulos, Y., Džeroski, S., and Kakas, A. (1997). Integrating explanatory and descriptive learning in ILP. In Proc. International Joint Conference on Artificial Intelligence, 2: 900-906.Morgan Kaufmann, CA.

Džeroski, S., Demšar, D., Grbović, J., and Walley, W. (1997). Learning to infer chemical parameters of river water quality from bioindicator data. In Proc. Sixth Electrotechnical and Computer Science Conference, pp. 129-132. Slovenian Section IEEE, Ljubljana, Slovenia.

Džeroski, S., and Erjavec, T. (1997). Induction of Slovene nominal paradigms. In Proc. Seventh International Workshop on Inductive Logic Programming, LNCS 1297: 141-148.

Džeroski, S., and Erjavec, T. Learning Slovene declensions with FOIDL. In Workshop Notes on Empirical Learning of Natural Language Processing Tasks (held at ECML 1997), pages 49-60. Prague, Czech Republic.

Džeroski, S., Grbović, J., Walley, W., and Demšar, D. (1997). A computer based reappraisal of bioindicator zone preferences and weights within the Saprobic Index using data from river quality surveys in Slovenia. In Proc. Fourth International Conference on Water Pollution, pp. 331-340. Computational Mechanics Publications, Southampton, UK.

Džeroski, S., Potamias, G., Moustakis, V., and Charissis, G. Automated revision of expert rules for treating acute abdominal pain in children. In Proc. Sixth Conference on Artificial Intelligence in Medicine Europe, LNCS 1211: 98-109.

Džeroski, S., Schulze-Kremer, S., Heidtke, K., Siems, K., and Wettschereck, D. (1997). Applying ILP to diterpene structure elucidation from 13C NMR spectra. In Proc. Sixth International Workshop, LNCS 1314: 41-54.

Kompare, B., Džeroski, S., and Karalič, A. (1997). Identification of the Lake of Bled ecosystem with the artificial intelligence tolls M5 and FORS. In Proc. Fourth International Conference on Water Pollution, pp. 789-798. Computational Mechanics Publications, Southampton, UK.

Kompare, B., Džeroski, S., and Križman, V. (1997). Modelling the growth of algae in the Lagoon of Venice with the artificial intelligence tool GoldHorn. In Fourth International Conference on Water Pollution, pp. 799-808. Computational Mechanics Publications, Southampton, UK.

Kontić, B., and Džeroski, S. (1997). Perspective of machine learning in epidemiological studies. In Proc. International Symposium on Environmental Epidemiology in Central and Eastern Europe: Critical Issues for Improving Health, 27 pages. International Society for Environmental Epidemiology, Smolenice, Slovak Republic.

Laer, W., Raedt, L., and Džeroski, S. (1997). On multi-class problem and discretization in inductive logic programming. In Proc. Tenth International Symposium on Foundations of Intelligent Systems, LNCS 1325: 277-286.

Todorovski, L., and Džeroski, S. (1997). Declarative bias in equation discovery. In Proc. Fourteenth International Conference on Machine Learning, pp. 376-384. Morgan Kaufmann, San Francisco, CA.

Todorovski, L., Džeroski, S., and Kompare, B. (1997). Automated modeling of phytoplankton growth using ecological domain knowledge. In Proc. Fourth International Conference on Water Pollution, pp. 533-542. Computational Mechanics Publications, Southampton, UK.

Zupan, B., and Džeroski, S. (1997). Acquiring and validating background knowledge for machine learning using function decomposition. In Proc. Sixth Conference on Artificial Intelligence in Medicine Europe, LNCS 1211: 86-97.

1996

Articles in Journals


Džeroski, S., and Lavrač, N. (1996). Rule induction and instance-based learning applied in medical diagnosis. Technology and Health Care, 4: 203-221.

Lavrač, N., Zupanič, D., Weber, I., Kazakov D., Štêpánková O., and Džeroski, S. (1996). ILPNET repositories on WWW: Inductive Logic Programming systems, datasets and bibliography. AI Communications, 9(4): 157-206.

Book chapters


Džeroski, S. (1996). Inductive logic programming and knowledge discovery in databases. In U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, editors. Advances in Knowledge Discovery and Data Mining, pages 118-152. AAAI Press, Cambridge, UK.

Džeroski, S., and Bratko, I. (1996). Applications of inductive logic programming. In L. De Raedt, editor. Advances in Inductive Logic Programming, pages 65-81. IOS Press, Amsterdam, 1996.

Lavrač, N., Džeroski, S., and Bratko, I. (1996). Handling imperfect data in inductive logic programming. In L. De Raedt, editor. Advances in Inductive Logic Programming, pages 48-64. IOS Press, Amsterdam, The Netherlands.

Conference/Workshop Contributions


Gamberger, D., Lavrač, N., and Džeroski, S. (1996). Noise elimination in inductive concept learning: a case study in medical diagnosis. In Proc. Seventh International Workshop on Algorithmic Learning Theory, LNCS 1160: 199-212.

Lavrač, N., Gamberger, D., and Džeroski, S. (1996). Noise elimination applied in early diagnosis of rheumatic diseases. In Proc. Twelfth European Conference on Artificial Intelligence, pp. 56-63. ECCAI, Budapest, Hungary.

Walley, W., and Džeroski, S. (1996). Biological monitoring: a comparison between Bayesian, neural and machine learning methods of water quality classification. In Proc. International Symposium on Environmental Software Systems, pp. 229-240. Chapman & Hall, London, UK.

1995

Articles in Journals


Bratko, I., and Džeroski, S. (1995). Engineering applications of ILP. New Generation Computing, 13: 313-333.

Džeroski, S., and Todorovski, L. (1995). Discovering dynamics: from inductive logic programming to machine discovery. Journal of Intelligent Information Systems, 4: 89-108.

Križman, V., Džeroski, S., and Kompare, B. (1995). Discovering dynamics from measured data. Elestrotechnical Review, 62(3/4): 191-198.

Book chapters


Džeroski, S., Muggleton, S., and Russell, S. (1995). PAC-learnability of constrained nonrecursive logic programs. In T. Petsche, S. Judd, and S. Hanson, editors. Computational Learning Theory and Natural Learning Systems, 3:243-255. The MIT Press, Cambridge, UK.

Conference/Workshop Contributions


Džeroski, S. (1995). Learing first-order clausal theories in the presence of noise. In Proc. Fifth Scandinavian Conference on Artificial Intelligence, pp.51-60. IOS Press, Amsterdam, The Netherlands.

Džeroski, S., and Grbović, J. (1995). Knowledge discovery in a water quality database. In Proc. First International Conference on Knowledge Discovery and Data Mining, pp. 81-86. AAAI Press, Menlo Park, CA.

Džeroski, S., Todorovski, L., and Urbančič, T. (1995). Handling real numbers in ILP: a step towards better behavioural clones. In Proc. Eighth European Conference on Machine Learning, LNCS 912: 283-286.

Kompare, B., and Džeroski, S. (1995). Getting more out of data: automated modelling of algal growth with machine learning. In Proc. International Symposium on Coastal Ocean Space Utilisation, pp. 209-220. University of Hawaii, HI.

Križman, V., and Džeroski, S. (1995). Discovering dynamics from measured data. In Proc. Eighth European Conference on Machine Learning, LNCS 912: 169-174.

Lavrač, N., Gamberger, D., and Džeroski, S. (1995). An approach to dimensionality reduction in learning from deductive databases. In Proc. Fifth International Workshop on Inductive Logic Programming, pp. 337-354. Leuven, Belgium.

1994

Articles in Journals


De Raedt, L., and Džeroski, S. (1994). First-order jk-clasual theories are PAC-learnable. Artificial Intelligence, 70: 375-392.

Kietz, J., and Džeroski, S. (1994). Inductive logic programming and learnbility. SIGART Bulletin, 5: 22-32.

Kompare, B., Bratko, I., Steinman, F., and Džeroski, S. (1994). Using machine learning techniques in the construction of models. Part 1, Introduction. Ecological Modelling, 75/76: 617-628.

Lavrač, N., and Džeroski, S. (1994). Weakening the language bias in LINUS. Journal of Experimental and Theoretical Artificial Intelligence, 6: 95-119.

Todorovski, L., and Džeroski, S. (1994). Modeling dynamic systems with machine discovery (In Slovenian). Electrotechnical Review, 61(1-2): 55-64.

Books


Lavrač, N., and Džeroski, S. (1994). Inductive logic programming: techniques and applications, Ellis Horwood, Chichester, UK.

Conference/Workshop Contributions


Džeroski, S., Dephase, L., Ruck, B., and Walley, W. (1994). Classification of river water quality using machine learning. In Proc. Fifth International Conference on Computer Techniques in Environmental Studies, I: 129-137. Computational Mechanics Publications, Southampton, UK.

Džeroski, S., Grbović, J., and Ličan-Miloševič, D. (1994). Analysis of water quality data with machine learning. In Proc. Third Electrotechnical and Computer Science Conference, B: 175-178. Slovenian Section IEEE, Ljubljana, Slovenia.

Džeroski, S., Petrovski, I. (1994). Discovering dynamics with genetic programming. In Proc. European conference on Machine Learning, LNCS 784: 347-350.

Džeroski, S., and Todorovski, L. (1994). Handling real numbers in inductive logic programming. In Proc. Third Electrotechnical and Computer Science Conference, B: 143-146. Slovenian Section IEEE, Ljubljana, Slovenia.

Kompare, B., and Džeroski, S. (1994). Two artificial intelligence methods for knowledge synthesis from environmental data. In Proc. Fifth International Conference on Computer Techniques in Environmental Studies, II: 265-272. Computational Mechanics Publications, Southampton, UK.

1993

Articles in Journals


Džeroski, S., Cestnik, B., and Petrovski, I. (1993). Using the m-estimate in rule induction. Journal of Computing and Information Technology, 1: 37-46.

Džeroski, S., and Lavrač, N. (1993). Inductive learning in deductive databases. IEEE Transactions on Knowledge and Data Engineering, 5(6): 939-949.

Lavrač, N., Džeroski, S., Pirnat, V., and Križman, V. (1993). The utility of background knowledge in learning medical diagnostic rules. Applied Artificial Intelligence, 7(3): 273-293.

Conference/Workshop Contributions


De Raedt, L., Lavrač, N., and Džeroski, S. Multiple predicate learning. In Proc. Third International Workshop on Inductive Logic Programming, pp. 221-240. Jožef Stefan Institute, Ljubljana, Slovenia.

De Raedt, L., Lavrač, N., and Džeroski, S. Multiple predicate learning. In Proc. Thirteenth International Joint Conference on Artificial Intelligence, 2:1037-1042. Morgan Kaufmann Publishers, San Mateo, CA.

Džeroski, S. (1993). Handling imperfect data in inductive logic programming. In Proc. Scandinavian Conference on Artificial Intelligence, pp. 111-125. IOS Press, Amsterdam, The Netherlands.

Džeroski, S., and Ličan, D. (1993). Modeling algal growth in the lagoon of Venice with regression trees. In Proc. Second Electrotechnical and Computer Science Conference, B: 205-208. Slovenian Section IEEE, Ljubljana, Slovenia.

Džeroski, S., and Todorovski, L. (1993). Modeling dynamic systems with machine discovery. In Proc. Second Electrotechnical and Computer Science Conference, B: 209-212. Slovenian Section IEEE, Ljubljana, Slovenia.

Džeroski, S., and Todorovski, L. (1993). Discovering dynamics. In Proc. Tenth International Conference on Machine Learning, pp. 97-103. Morgan Kaufmann, San Mateo, CA.

Džeroski, S., and Todorovski, L. (1993). Discovering dynamics: form inductive logic programming to machine discovery.

1992

Articles in Journals


Džeroski,S. (1992). Learning qualitative models with inductive logic programming. Informatica, 16: 30-41.

Book chapters


Džeroski, S., and Lavrač, N. (1992). Refinement graphs for FOIL and LINUS. In S.H. Muggleton, editor. Inductive Logic Programming, pages 319-333. Academic Press, London, UK.

Lavrač, N., and Džeroski, S. (1992). Inductive learning of relations from noisy examples. In S.H. Muggleton, editor. Inductive Logic Programming, pages 495-516. Academic Press, London, UK.

Conference/Workshop Contributions


Džeroski, S., Muggleton, S., and Russel, S. (1992). PAC-learnability of determinate logic programs. In Proc. Fifth ACM Workshop on Computational Learning Theory, pp. 128–135. ACM Press, New York, NY.

Lavrač, N., Cestnik, B., and Džeroski, S. (1992). Use of heuristics in empirical inductive logic programming. In Proc. International Workshop on Inductive Logic Programming, 17 pages. Tokyo, Japan.