Publications sorted by category

Publications sorted by year

Journal articles

• H. Blockeel, S. Dzeroski, B. Kompare, S. Kramer, B. Pfahringer, and W. Van Laer. Experiments in predicting biodegradability. Applied Artificial Intelligence, 18: 157-181, 2004.
  
  
full article 236 k



• S. Dzeroski, and B. Zenko. Is combining classifiers better than selecting the best one? Machine Learning, 54: 255-273, 2004.
  
  
full article 108 k



• T. Erjavec, and S. Dzeroski. Machine learning of morphosyntactic structure: Lemmatizing unknown Slovene words. Applied Artificial Intelligence, 18: 17-41, 2004.
  
  
full article 147 k

Workshop proceedings

• J.-F. Boulicaut and S. Dzeroski, editors. Proceedings of the Second International Workshop on Knowledge Discovery in Inductive Databases (ECML/PKDD-2003). Institut Rudjer Boskovic, Zagreb, 2003.
  
  
full proceedings 2.069 k



• S. Dzeroski, L. de Raedt and S. Wrobel, editors. Proceedings of the Second International Workshop on Multi-Relational Data Mining. Washington, DC, 2003.
  
  
full proceedings 3.370 k

Book chapter

• S. Dzeroski. Relational reinforcement learning for agents in worlds with objects. In E. Alonso, D. Kudenko, D. Kazakov, editors, Adaptive Agents and Multi-Agent Systems, pages 306-321. Springer, Berlin, 2003.
  
  full article 219 k
  
  
  

Journal articles

• S. Dzeroski. Multi-relational data mining: An introduction. SIGKDD Explorations, 5: 1-16, 2003.
  
  
full paper 55 k



• S. Dzeroski, and D. Drumm. Using regression trees to identify the habitat preference of the sea cucumber (Holothuria leucospilota) on Rarotonga, Cook Island. Ecological Modelling, 170: 219-226, 2003.
  
  
full article 147 k



• S. Dzeroski, and L. Todorovski. Learning population dynamics models from data and domain knowledge. Ecological Modelling, 170: 129-140, 2003.
  
  
full article 121 k



• K. Jerina, M. Debeljak, S. Dzeroski, A. Kobler, and M. Adamic. Modeling the brown bear population in Slovenia: A tool in the conservation management of a threatened species. Ecological Modelling, 170: 453-469, 2003.
  
  
full article 360 k



• L. Todorovski, and S. Dzeroski. Combining classifiers with meta decision trees. Machine Learning, 50: 223-249, 2003.
  
  
full article 190 k



• L. Todorovski, S. Dzeroski, P. Langley, and C. S. Potter. Using equation discovery to revise an Earth ecosystem model of the carbon net production. Ecological Modelling, 170: 141-154, 2003.
  
  
full article 185 k



• B. Zmazek, L. Todorovski, S. Dzeroski, J. Vaupotic, and I. Kobal. Application of decision trees to the analysis of soil radon data for earthquake prediction. Applied radiation and isotopes, 58: 697-706, 2003.
  
  
full article 239 k

Published (conference) papers

• D. Demsar, S. Dzeroski, T. Larsen, and P. H. Krogh. Identifying the most important agricultural factors for the soil community of microathropods. In Proc. Twelfth International Electrotechnical and Computer Science Conference, Volume B, pages 369-372. Slovenia Section IEEE, Ljubljana, 2003.
  
  
• S. Dzeroski, L. Todorovski, and P. Ljubic. Inductive databases of polynomial equations. In Proc. Second International Workshop on Knowledge Discovery in Inductive Databases, the Fourteenth European Conference on Machine Learning and the Seventh European Conference on Principles and Practice of Knowledge Discovery in Databases, pages 28-43. Institut Rudjer Boskovic, Zagreb, Croatia, 2003.
  
  
full paper 335 k



• S. Dzeroski, L. Todorovski, and P. Ljubic. Using constraints in discovering dynamics. In Proc. Sixth International Conference on Discovery Science, pages 297-305. Springer, Berlin, 2003.
  
  
• S. Dzeroski, L. Todorovski, B. Zmazek, J. Vaupotic, and I. Kobal. Modelling soil radon concentration for earthquake prediction. In Proc. Sixth Workshop on Mining Scientific and Engineering Databases (SDM-2003), pages 19-28. San Francisco, CA, 2003.
  
  
• S. Dzeroski, L. Todorovski, B. Zmazek, J. Vaupotic, and I. Kobal. Modelling soil radon concentration for earthquake prediction. In Proc. Sixth International Conference on Discovery Science, pages 87-99. Springer, Berlin, 2003.
  
  
• T. Erjavec, and S. Dzeroski. Lemmatising unknown words in highly inflective languages. In Proc. International Workshop on Information Extraction for Slavonic and other Central and Eastern European Languages, pages 70-76. Context, Sofia, 2003.
  
  
• L. Todorovski, and S. Dzeroski. Revision of equation-based models. In Proc. Sixth Workshop on Mining Scientific and Engineering Databases (SDM-2003), pages 79-88. San Francisco, CA, 2003.
  
  
full paper 232 k



• L. Todorovski, and S. Dzeroski. Using domain specific knowledge for automated modeling. In Proc. Fifth International Conference on Intelligent Data Analysis, pages 48-59. Springer, Berlin, 2003.
  
  
full paper 193 k



• L. Todorovski, S. Dzeroski, and P. Ljubic. Discovery of polynomial equations for regression. In Proc. Sixth International Multi-Conference Information Society, Volume A, pages 151-154. Jozef Stefan Institute, Ljubljana, 2003.
  
  



• F. Zelezny, N. Lavrac, and S. Dzeroski. Constraint-based relational subgroup discovery. In Proc. Second International Workshop on Multi-Relational Data Mining (KDD-2003), pages 135-150. Washington, DC, 2003.
  
  
• B. Zenko, and S. Dzeroski. Combining classifiers with stacking. In Proc. Twelfth International Electrotechnical and Computer Science Conference, Volume B, pages 467-470. Slovenia Section IEEE, Ljubljana, 2003. In Slovenian.
  
  
• B. Zenko, S. Dzeroski, A. B. Kobal, D. Kobal Grum, N. Arneric, J. Osredkar, and M. Horvat. Relating personality traits and mercury exposure in miners with machine learning methods: A preliminary study. In Proc. Sixth International Multi-Conference Information Society, Volume A, pages 163-166. Jozef Stefan Institute, Ljubljana, 2003.
  
  

Other published work

• I. Bratko, S. Dzeroski, and B. Kompare. Analysis of Environmental Data with Machine Learning Methods, I. Jozef Stefan Institute, Ljubljana, Slovenia, 2003. Teaching Material.
  
  
• I. Bratko, S. Dzeroski, and B. Kompare. Analysis of Environmental Data with Machine Learning Methods, II. Jozef Stefan Institute, Ljubljana, Slovenia, 2003. Teaching Material.
  
  
• S. Dzeroski. Environmental Applications of Data Mining and Knowledge Discovery: Lecture Notes of a PhD-level Course. Universita degli Studi di Trento, Trento, 2003.
  
  
• S. Dzeroski. Relational data mining: Lecture Notes of a PhD-level Course. Universita degli Studi di Pisa, Pisa, 2003.
  
  
• S. Dzeroski, M. Bohanec, and B. Zupan. Data Mining and Decision Support for Environmental Applications: Lecture Notes, Jozef Stefan Institute, Ljubljana, Slovenia, 2003.
  
  
• S. Dzeroski, and L. de Raedt. Multi-relational data mining. The Ninth International Conference on Knowledge Discovery and Data Mining (KDD-2003): Tutorial Notes. The Association for Computing Machinery, New York, 2003.
  
  
• S. Dzeroski, and L. de Raedt. Multi-relational data mining: A workshop report. SIGKDD Explorations, 4: 122-124, 2003.
  
  
full paper 196 k



• S. Dzeroski, and B. Zenko. A report on the Summer school on relational data mining: 17-18 August 2002, Helsinki, Finland. SIGKDD explorations, Volume 5, pages 100-101, 2003.
  
  
full paper 32 k



• M. Grobelnik, N. Lavrac, D. Mladenic, M. Mohorcic, B. Cestnik, and S. Dzeroski. Successfully applying for projects in the 6FP of the EU. Jozef Stefan Institut, 2003.
  
  
• C. Kamath, M. F. Hancock, S. Dzeroski, M. Ankerst, D. A. Keim, and J. Ghosh. Third SIAM International Conference on Data Mining: Tutorial notes. University of Illinois, Chicago, 2003.
  
  
• B. Peterlin, T. Kunej, D. Hristovski, and S. Dzeroski. Analysis of the Y chromosome micro deletion database (ycmdb) for genotype correlations. In Proc. Genetics of male infertility: From research to clinic, page 84, University of Florence, Florence, 2003. Abstract.
  
  
• B. Peterlin, T. Kunej, D. Hristovski, and S. Dzeroski. Prognostic value of Y chromosome micro deletions for sperm retrieval. In Final programme and abstracts, European Journal of Human Genetics, Volume 11(1), page 132, European Society of Human Genetics, Birmingham, 2003. Abstract.
  
  
• L. Todorovski, S. Dzeroski, and P. Ljubic. Discovery of polynomial equations for regression. In Program and abstracts, International Conference on Methodology and Statistics, pages 67-70, Center of Methodology and Informatics, Institute of Social Sciences at Faculty of Social Sciences, Ljubljana, 2003. Abstract.
  
  
• F. Zelezny, N. Lavrac, and S. Dzeroski. Using constraints in relational subgroup discovery. In Program and abstracts, International Conference on Methodology and Statistics, pages 68-70, Center of Methodology and Informatics, Institute of Social Sciences at Faculty of Social Sciences, Ljubljana, 2003. Abstract.
  
  

Workshop proceedings

• S. Dzeroski, L. de Raedt, and S. Wrobel, editors. Proceedings of the Workshop on Multi-Relational Data Mining (KDD-2002). ACM, 2002.
  
  
SIGKDD link



• S. Dzeroski, and B. Zenko, editors. Summer school on relational data mining: Lecture notes. University of Helsinki, Helsinki, 2002.
  
  
more

Book chapters

• S. Dzeroski. Environmental sciences. In W. Klösgen, and J. M. Zytkow, editors. Handbook of Data Mining and Knowledge Discovery, pages 817-830. Oxford University Press, Oxford, 2002.
  
  
• S. Dzeroski. 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, 2002.
  
  
• S. Dzeroski, and L. Todorovski. 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, 2002.
  
  

Journal article

• B. Zenko, and S. Dzeroski. Predicting biodegradability with regression trees. Electrotechnical Journal 69(1): 60-68, 2002. In Slovenian.
  
  
full article 159 k

Published (conference) papers

• H. Blockeel, M. Bruynooghe, S. Dzeroski, J. Ramon, and J. Struyf. Hierarchical multi-classification. In Proc. First International Workshop on Multi-Relational Data Mining (KDD-2003), pages 21-35. Edmonton, Canada, 2002.
  
  
full paper 242 k



• K. Driessens, and S. Dzeroski. Integrating experimentation and guidance in relational reinforcement learning. In Proc. Nineteenth International Conference on Machine Learning, pages 115-122. Morgan Kaufmann, San Francisco, 2002.
  
  
full paper 262 k | extended abstract 75 k



• K. Driessens, and S. Dzeroski. On using guidance in relational reinforcement learning. In Proc. Twelfth Belgian-Dutch Conference on Machine Learning, pages 31-38. Faculty of Mathematics and Computer Science, University of Utrecht, Utrecht, 2002.
  
  
full paper 209 k



• S. Dzeroski. Learning in rich representations: Inductive logic programming and computational scientific discovery. In Proc. Twelfth International Conference on Inductive logic programming, pages 346-349. Springer, Berlin, 2003.
  
  
full paper 63 k | slides 194 k



• S. Dzeroski. Computational scientific discovery and inductive databases. In Proc. Workshop on Active Mining (ICDM-2002), pages 4-15. Maebashi, Japan, 2002.
  
  
full paper 11 k | slides 186 k



• S. Dzeroski. Learning in rich representation: Inductive logic programming and computational scientific discovery. In Proc. Nineteenth International Conference on Machine Learning, pages 701-702. Morgan Kaufmann, San Francisco, 2002.
  
  
• S. Dzeroski. Relational reinforcement learning for agents in worlds with objects. In Proc. Symposium on Adaptive Agents and Multi-Agent Systems (AISB'02), pages 1-8. The Society for the Study of Artificial Intelligence and Simulation of Behaviour, Imperial College, London, 2002.
  
  
full paper 125 k



• S. Dzeroski, L. Todorovski, and H. Blockeel. Relational ranking with predictive clustering trees. In Proc. Workshop on Active Mining (ICDM-2002), pages 9-15. Maebashi, Japan, 2002.
  
  
full paper 80 k



• S. Dzeroski, and B. Zenko. Is combining classifiers better than selecting the best one? In Proc. Nineteenth International Conference on Machine Learning, pages 123-129. Morgan Kaufmann, San Francisco, 2002.
  
  
full paper 124 k



• S. Dzeroski, and B. Zenko. Stacking with multi-response model trees. In Proc. Third International Workshop on Multiple classifier systems, pages 201-211. Springer, Berlin, 2002.
  
  
full paper 108 k



• P. Langley, J. Sanchez, L. Todorovski, and S. Dzeroski. Inducing process models from continuous data. In Proc. Nineteenth International Conference on Machine Learning, pages 347-354. Morgan Kaufmann, San Francisco, 2002.
  
  
full paper 184 k



• L. Todorovski, H. Blockeel, and S. Dzeroski. Ranking with predictive clustering trees. In Proc. Thirteenth European Conference on Machine Learning, pages 444-455. Springer, Berlin, 2002.
  
  
full paper 190 k



• L. Todorovski, B. Cestnik, M. Kline, N. Lavrac, and S. Dzeroski. 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 (ECM/PKDD-2002), pages 141-149. Helsinki University, Helsinki, 2002.
  
  
• L. Todorovski, B. Cestnik, M. Kline, N. Lavrac, and S. Dzeroski. Qualitative clustering of short time series: A case study of firms reputation data. In Proc. Fifth International Multi-Conference Information Society, Volume A, pages 143-146. Jozef Stefan Institute, Ljubljana, Slovenia, 2002.
  
  
• Z. Zabokrtsky, P. Sgall, and S. Dzeroski. A machine learning approach to automatic functor assignment in the Prague Dependency Treebank. In Proc. Third International Conference on Language Resources and Evaluation, Volume V, pages 1513-1520. European Language Resources Association, Grand Canaria, 2002.
  
  
• B. Zenko, and S. Dzeroski. Stacking with an extended set of meta-level attributes and MLR. In Proc. Thirteenth European Conference on Machine Learning, pages 493-504. Springer, Berlin, 2002.
  
  
full paper 114 k

Technical reports

• S. Dzeroski, H. Blockeel, and L. Todorovski. Relational ranking with predictive clustering trees, Technical report IJS-DP-8639. Jozef Stefan Institute, Ljubljana, Slovenia, 2002.
  
  
• B. Zenko, L. Todorovski, and S. Dzeroski. Experiments with heterogeneous meta decision trees, Technical report IJS-DP-8638. Jozef Stefan Institute, Ljubljana, Slovenia, 2002.
  
  

Other published work

• S. Dzeroski. Relational data mining. In Book of abstracts, TARSKI meeting of the COST 274. COST, 2002. Abstract.
  
  
• S. Dzeroski. RDM applications: An overview. In S. Dzeroski, and B. Zenko, editors. Summer school on relational data mining: Lecture notes. University of Helsinki, Helsinki, 2002.
  
  
slides 121 k



• S. Dzeroski. Relational data mining: A quick introduction. In S. Dzeroski, and B. Zenko, editors. Summer school on relational data mining: Lecture notes. University of Helsinki, Helsinki, 2002.
  
  
slides 43 k

Other unpublished work

• I. Bratko, S. Dzeroski, and B. Kompare. Analysis of Environmental Data with Machine Learning Methods, I. Jozef Stefan Institute, Ljubljana, Slovenia, 2002. Teaching Material.
  
  
• I. Bratko, S. Dzeroski, and B. Kompare. Analysis of Environmental Data with Machine Learning Methods, II. Jozef Stefan Institute, Ljubljana, Slovenia, 2002. Teaching Material.
  
  
• S. Dzeroski. Relational data mining: IEEE International Conference on Data Mining tutorial. Maebashi City, Japan, IEEE, 2002.
  
  

Edited book

• S. Dzeroski, and N. Lavrac, editors. Relational Data Mining. Springer, Berlin, 2001.
  
  
more

Book chapters

• S. Dzeroski. Data mining in a nutshell. In S. Dzeroski, N. Lavrac, editors, Relational Data Mining, pages 3-27. Springer, Berlin, 2001.
  
  
more



• S. Dzeroski. Relational data mining applications: An overview. In S. Dzeroski, N. Lavrac, editors, Relational Data Mining, pages 339-364. Springer, Berlin, 2001.
  
  
more



• S. Dzeroski, and N. Lavrac. An introduction to inductive logic programming. In S. Dzeroski, N. Lavrac, editors, Relational Data Mining, pages 48-73. Springer, Berlin, 2001.
  
  
more



• L. Todorovski, I. Weber, N. Lavrac, O. Stepankova, S. Dzeroski, D. Kazakov, D. Zupanic, and P. Flach. Internet resources on ILP for KDD. In S. Dzeroski, N. Lavrac, editors, Relational Data Mining, pages 375-388. Springer, Berlin, 2001.
  
  
more

Journal articles

• J. Comas, S. Dzeroski, K. Gibert, I. R.-Roda, and M. Sanchez-Marre. Knowledge discovery by means of inductive methods in wastewater treatment plant data. AI Communications, 14: 45-62, 2001.
  
  
full article 6.154 k



• M. Debeljak, S. Dzeroski, K. Jerina, A. Kobler, and M. Adamic. Habitat suitability modeling for red deer (Cervus elaphus L.) in South-Western Slovenia with classification trees. Ecological Modelling, 138: 321-330, 2001.
  
  
full article 119 k



• S. Dzeroski. Applications of symbolic machine learning to ecological modelling. Ecological Modelling, 146: 263-273, 2001.
  
  
full article 173 k



• S. Dzeroski, L. de Raedt, and K. Driessens. Relational reinforcement learning. Machine Learning, 43: 7-52, 2001.
  
  
full article 368 k



• S. Dzeroski, and Z. Zabokrtsky. A machine learning approach to automatic functor assignment in the Prague Dependency Treebank. Prague Bulletin of Mathematical Linguistics, 76: 35-43, 2001.
  
  
full article 654 k



• B. Kompare, L. Todorovski, and S. Dzeroski. Modeling and prediction of phytoplankton growth with equation discovery: Case study - Lake Glumso, Denmark. Verhandlungen - Internationale Vereinigung fuer Theoretische und Angewandte Limnologie, 27: 3626-3631, 2001.
  
  
full article 503 k



• W. J. Walley, J. Grbovic, and S. Dzeroski. A reappraisal of saprobic values and indicator weights based on Slovenian river quality data. Water resources, 35: 4285-4292, 2001.
  
  
full article 126 k

Published (conference) papers

• S. Dzeroski, and J. Grbovic. Relating biodiversity of river communities to physical and chemical water properties. In Sustainability in the information society (Fifteenth International Symposium on Informatics for Environmental Protection), Part 1, pages 367-372. Marburg, Metropolis, 2001.
  
  
full paper 307 k



• S. Dzeroski, D. Hristovski, and B. Peterlin. 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, Volume A, pages 103-107. Jozef Stefan Institute, Ljubljana, Slovenia, 2001.
  
  
full paper 2.829 k



• S. Dzeroski, and P. Langley. Computational discovery of communicable knowledge: Symposium report. In Proc. Fourth International Conference on Discovery Science, pages 45-49. Springer, Berlin, 2001.
  
  
full paper 80 k



• S. Dzeroski, and L. Todorovski. Integrating knowledge-based and data-driven modeling of population dynamics. In Sustainability in the information society (Fifteenth International Symposium on Informatics for Environmental Protection), Part 2, pages 653-658. Marburg, Metropolis, 2001.
  
  
full paper 295 k



• D. Hristovski, J. Stare, B. Peterlin, and S. Dzeroski. Biomedical discovery support system. Information System in Health Care, pages 1-5, 2001.
  
  
• D. Hristovski, J. Stare, B. Peterlin, and S. Dzeroski. Supporting discovery in medicine by association rule mining in Medline and UMLS. In Proc. Tenth World Congress on Medical Informatics. IOS Press, Amsterdam, Netherlands, 2001.
  
  
full paper 252 k



• L. Todorovski, and S. Dzeroski. Theory revision in equation discovery. In Proc. Fourth International Conference on Discovery Science, pages 390-400. Springer, Berlin, 2001.
  
  
full paper 155 k



• L. Todorovski, and S. Dzeroski. Using domain knowledge on population dynamics modeling for equation discovery. In Proc. Twelfth European Conference on Machine Learning, pages 478-490. Springer, Berlin, 2001.
  
  
full paper 143 k



• B. Zenko, L. Todorovski, and S. Dzeroski. A comparison of stacking with meta decision trees to bagging, boosting, and stacking with other methods. In Proc. IEEE International Conference on Data Mining, pages 669-670. IEEE Computer Society, Los Alamitos, 2001.
  
  
full paper 37 k



• B. Zenko, L. Todorovski, and S. Dzeroski. A comparison of stacking with meta decision trees to other combining methods. In Proc. Fourth International Multi-Conference Information Society, Volume A, pages 144-147. Jozef Stefan Institute, Ljubljana, Slovenia, 2001.
  
  
full paper 73 k



• B. Zenko, L. Todorovski, and S. Dzeroski. A comparison of stacking with MDTs to bagging, boosting, and other stacking methods. In Proc. Workshop on Integrating Aspects of DM, DS and ML (ECM/PKDD-2001), pages 163-174. Freiburg, Germany, 2001.
  
  
full paper 113 k

Other published work

• S. Dzeroski, and D. Drumm. Using machine learning to identify the habitant preference of the sea cucumber, Holothria leucospilota on Rarotonga, Cook Islands. In Conference programme, book of abstracts and list of participants, Third European Ecological Modelling Conference, page 10, International Society for Ecological Modelling, Zagreb, Croatia, 2001. Abstract.
  
  
abstract 45 k



• S. Dzeroski, J. Grbovic, and H. Blockeel. Predicting river water communities with logical decision trees. In Abstract book, Second Symposium for European Freshwater Sciences, page 49, University Paul Sabatier, Toulouse, France, 2001. Abstract.
  
  
abstract 69 k



• S. Dzeroski, J. Grbovic, and H. Blockeel. Predicting river water communities with logical decision trees. In Conference programme, book of abstracts and list of participants, Third European Ecological Modelling Conference, page 11, International Society for Ecological Modelling, Zagreb, Croatia, 2001. Abstract.
  
  
abstract 56 k



• S. Dzeroski, and L. Todorovski. Encoding and using knowledge on population dynamics processes for equation discovery. In Conference programme, book of abstracts and list of participants, Third European Ecological Modelling Conference, page 12, International Society for Ecological Modelling, Zagreb, Croatia, 2001. Abstract.
  
  
abstract 51 k



• S. Dzeroski, and L. Todorovski. Encoding domain knowledge on population dynamics modeling for equation discovery. In Abstracts, Model-based reasoning, page 27, Pavia, Italy, 2001. Abstract.
  
  
abstract 99 k



• P. Goethals, S. Dzeroski, A. Dedecker, N. Raes, V. Adriaenssens, W. Gabriels, and N. de Pauw. Comparing classification trees, artificial neural networks and fuzzy logic models to predict macroinvertebrate communities in the Zwalm river basin (Flanders, Belgium). In Abstract book, Second Symposium for European Freshwater Sciences, page 66, University Paul Sabatier, Toulouse, France, 2001. Abstract.
  
  
• D. Hristovski, B. Peterlin, and S. Dzeroski. Literature based discovery support system and its application to disease gene identification. Journal of the American Medical Informatics Association, page 928, 2001. Abstract.
  
  
• K. Jerina, M. Debeljak, S. Dzeroski, A. Kobler, and M. Adamic. Modelling the parameters of brown bear population in Slovenia - a tool in the conservation management of threatened species. In Conference programme, book of abstracts and list of participants, Third European Ecological Modelling Conference, page 13, International Society for Ecological Modelling, Zagreb, Croatia, 2001. Abstract.
  
  
abstract 77 k



• L. Todorovski, S. Dzeroski, P. Langley, and C. S. Potter. Using equation discovery to revise an earth ecosystem model of the carbon net production. In Conference programme, book of abstracts and list of participants, Third European Ecological Modelling Conference, page 43, International Society for Ecological Modelling, Zagreb, Croatia, 2001. Abstract.
  
  
abstract 38 k

Edited book

• J. Cussens, and S. Dzeroski, editors. Learning Language in Logic. Springer, Berlin, 2000. Lecture Notes in Artificial Intelligence, 1925.
  
  
springer link

Book chapters

• S. Dzeroski, J. Cussens, S. Manandhar. An introduction to inductive logic programming and learning language in logic. In J. Cussens, and S. Dzeroski, editors, Learning Language in Logic, pages 3-35. Springer, Berlin, 2000.
  
  
full chapter 252 k



• S. Dzeroski, and T. Erjavec. Learning to lemmatise Slovene words. In J. Cussens, and S. Dzeroski, editors, Learning Language in Logic, pages 69-88. Springer, Berlin, 2000.
  
  
full chapter 149 k

Journal articles

• S. Dzeroski, D. Demsar, and J. Grbovic. Predicting chemical parameters of river water quality from bioindicator data. Applied Intelligence, 13(1): 7-17, 2000.
  
  
full article 1.918 k



• S. Dzeroski, D. Hristovski, and B. Peterlin. Using data mining and OLAP to discover patterns in a database of patients with Y-chromosome deletions. Journal of the American Medical Informatics Association, pages 215-219, 2000.
  
  
full article 63 k



• D. Gamberger, N. Lavrac, and S. Dzeroski. Noise detection and elimination in preprocessing: Experiments in medical domains. Applied Artificial Intelligence, 14(2): 205-223, 2000.
  
  
full article 295 k



• C. Kampichler, S. Dzeroski, and R. Wieland. The application of machine learning techniques to the analysis of soil ecological data bases: Relationships between habitat features and Collembola community characteristics. Soil Biology and Biochemistry 32: 197-209, 2000.
  
  
full article 384 k

Published (conference) papers

• J. Comas, S. Dzeroski, and M. Sanchez-Mare. Applying machine learning methods to wastewater treatment plant data. In Proc. Second Workshop on Binding Environmental Science and Artificial Intelligence. Berlin, Germany, 2000.
  
  
full paper 4.531 k



• S. Dzeroski, T. Erjavec, and J. Zavrel. Morphosyntactic tagging of Slovene: Evaluating taggers and tagsets. In Proc. Second International Conference on Language Resources and Evaluation, Volume II, pages 1099-1104. National Technical University of Athens, Greece, 2000.
  
  
full paper 67 k



• S. Dzeroski, D. Hristovski, T. Kunej, and B. Peterlin. 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. Hannover, Germany, 2000.
  
  
• D. Hristovski, S. Dzeroski, B. Peterlin, and A. Rozic-Hristovski. 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, pages 446-451. Springer, Berlin, 2000.
  
  
full paper 7.059 k



• D. Hristovski, B. Peterlin, and S. Dzeroski. Discovery support system for medicine and genetics. In Proc. Second Congress of Genetic Society of Slovenia with International Participation, pages 231-232. Genetic Society Slovenia, Ljubljana, Slovenia, 2000.
  
  
• A. Kobler, M. Hocevar, and S. Dzeroski. Forest border identification by rule-based classification of LandSat TM and GIS data. In Proc. Workshop International Cooperation and Technology Transfer (International Archives of Photogrammetry and Remote Sensing, Volume XXXII, Part 6W8/1), pages 93-100. RICS Books, London, 2000.
  
  
full paper 3.316 k



• A. Kobler, M. Hocevar, and S. Dzeroski. Forest border identification by rule-based classification of landsat TM and GIS data. In Proc. Workshop on Machine Learning of Spatial Knowledge (ICML-2000), Stanford University, 2000.
  
  
• A. Kobler, M. Hocevar, and S. Dzeroski. Mapping spontaneous afforestation 1981-1995 in Slovenia by remote sensing and GIS. In Proc. International conference on GIS for Earth science applications, 8 pages. Menemen-Izmir, Turkey, 2000.
  
  
• L. Todorovski, and S. Dzeroski. Combining multiple models with meta decision trees. In Proc. Fourth European Conference on Principles and Practice of Knowledge Discovery in Databases, pages 54-64. Springer, Berlin, 2000.
  
  
full paper 194 k



• L. Todorovski, and S. Dzeroski. Combining two aspects of meta-learning with heterogeneous meta decision trees. In Proc. Fifth International Workshop on Multistrategy Learning, pages 221-232. Universidade do Porto, Portugal, 2000.
  
  
full paper 767 k



• L. Todorovski, S. Dzeroski, A. Srinivasan, J. Whiteley, and D. Gavaghan. Discovering the structure of partial differential equations from example behaviour. In Proc. Seventeenth International Conference on Machine Learning, pages 991-998. Morgan Kaufmann, San Francisco, CA, 2000.
  
  
full paper 214 k



• B. Zenko, and S. Dzeroski. Predicting biodegradability with regression trees. In Proc. Ninth Electrotechnical and Computer Science Conference, Volume B, pages 275-278. Slovenia Section IEEE, Ljubljana, Slovenia, 2000. In Slovene.
  
  
full paper 107 k

Other published work

• S. Dzeroski. Applications of symbolic machine learning. In Abstract book, Second International Conference on Applications of Machine Learning to Ecological Modelingpage 33, Adelaide University, Australia, 2000. Abstract.
  
  
• D. Hristovski, B. Peterlin, and S. Dzeroski. Discovery support system: Approach to gene identification and pathogenesis. In Programme, Abstracts, Life sciences 2000, page 150, Slovenian Society for Stereology and Quantitative Image Analysis, Ljubljana, Slovenia, 2000. Abstract.
  
  
• A. Kobler, M. Hocevar, and S. Dzeroski. Forest border identification by rule-based classification of landsat TM and GIS data. In Collection of Abstracts, International Society for Photogrammetry and Remote Sensing WG VI/3 and IV/3 Workshop, page 35, Institute of Geodesy, Cartography and Photogrammetry, Ljubljana, Slovenia, 2000. Abstract.
  
  
• A. Kobler, M. Hocevar, and S. Dzeroski. Mapping spontaneous afforestation 1981-1995 in Slovenia by remote sensing and GIS. In Proc. International conference on GIS for Earth science applications, page 45. Menemen-Izmir, Turkey, 2000. Abstract.
  
  

Other unpublished work

• I. Bratko, S. Dzeroski, B. Kompare, and T. Urbancic. Analysis of Environmental Data with Machine Learning Methods I. Jozef Stefan Institute, Ljubljana, Slovenia, 2000. Teaching Material.
  
  
• I. Bratko, S. Dzeroski, B. Kompare, and T. Urbancic. Analysis of Environmental Data with Machine Learning Methods II. Jozef Stefan Institute, Ljubljana, Slovenia, 2000. Teaching Material.
  
  
• S. Dzeroski, D. Hristovski, R. King, A. Srinivasan, and B. Zupan. Data analysis in life sciences. I. Jozef Stefan Institute, Ljubljana, Slovenia, 2000. Teaching material
  
  
• S. Dzeroski, D. Hristovski, R. King, A. Srinivasan, and B. Zupan. Data analysis in life sciences. II. Jozef Stefan Institute, Ljubljana, Slovenia, 2000. Teaching material
  
  
• L. Todorovski, and S. Dzeroski. Combining multiple models with meta decision trees. Presented at SCML, European Conference on Machine Learning, May 30 - June 2, Barcelona, Catalonia, Spain, 2000.
  
  

Conference proceedings

• I. Bratko, and S. Dzeroski, editors. Machine Learning: Proceedings of the Sixteenth International Conference on Machine Learning, Bled, Slovenia, June 1999. Morgan Kaufmann, San Francisco, 1999.
  
  
amazon link



• S. Dzeroski, and P. Flach, editors. Proceedings of the Ninth International Workshop on Inductive Logic Programming, Bled, Slovenia, June 1999. Springer, Berlin, 1999. Lecture Notes in Artificial Intelligence, 1634.
  
  
springer link

Book chapter

• S. Dzeroski, L. Todorovski, I. Bratko, B. Kompare, and V. Krizman. Equation discovery with ecological applications. In A. H. Fielding, editor, Machine Learning Methods for Ecological Applications, pages 185-207. Kluwer, Dordrecht, 1999.
  
  

Journal articles

• M. Debeljak, S. Dzeroski, and M. Adamic. 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(1): 51-61, 1999.
  
  
full article 138 k



• N. Lavrac, S. Dzeroski, and M. Numao. Inductive logic programming for relational knowledge discovery. New Generation Computing 17: 3-23, 1999.
  
  
full article 3.106 k

Published (conference) papers

• H. Blockeel, S. Dzeroski, and J. Grbovic. 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, pages 15-18. Springer, Berlin, 1999.
  
  
full paper 170 k



• J. Cussens, S. Dzeroski, and T. Erjavec. Morphosyntactic tagging of Slovene using Progol. In Proc. Ninth International Conference on Inductive Logic Programming, pages 68-79. Springer, Berlin, 1999.
  
  
full paper 134 k



• J. Dimec, S. Dzeroski, L. Todorovski, and D. Hristovski. WWW search engine for Slovenian and English medical documents. In Proc. Fifteenth International Congress for Medical Informatics, pages 547-552. IOS Press, Amsterdam, 1999.
  
  
full paper link



• J. Dimec, L. Todorovski, D. Hristovski, and S. Dzeroski. A personalised search engine for Slovenian and English medical documents. In Managing Multimedia Collections, Twenty-third Library Systems Seminar, pages 56-63. Bled, Slovenia, 1999.
  
  
full paper link



• S. Dzeroski, H. Blockeel, B. Kompare, S. Kramer, B. Pfahringer, and W. van Laer. Experiments in predicting biodegradability. In Proc. Ninth International Conference on Inductive Logic Programming, pages 80-91. Springer, Berlin, 1999.
  
  
full paper 134 k



• S. Dzeroski, and L. Todorovski. Experiments in meta-level learning with ILP. In Proc. Third European Conference on Principles of Data Mining and Knowledge Discovery, pages 98-106. Springer, Berlin, 1999.
  
  
full paper 165 k



• V. Krizman, M. Gams, and S. Dzeroski. Discovering dynamics from data. In Proc. Second International Multi-Conference Information Society, pages PS/119-123. Jozef Stefan Institute, Ljubljana, Slovenia, 1999.
  
  
full paper 155 k

Technical reports

• H. Blockeel, S. Dzeroski, and J. Grbovic. Experiments with TILDE in the river water quality domain, Technical Report IJS-DP-8089. Jozef Stefan Institute, Ljubljana, Slovenia, 1999.
  
  
• S. Dzeroski, T. Erjavec, and J. Zavrel. Morphosyntactic tagging of Slovene: Evaluating PoS taggers and tagsets, Technical Report IJS-DP-8018. Jozef Stefan Institute, Ljubljana, Slovenia, 1999.
  
  

Other published work

• S. Dzeroski. Discovering useful knowledge from heaps of data. Delo, 41(143): 15, June 23, 1999. In Slovenian.
  
  
• M. Debeljak, S. Dzeroski, A. Kobler, and M. Adamic. Habitat suitability modeling and prediction for a population of red deer (Cervus elaphus L.) in South-Western Slovenia. In Book of abstracts, Conference programme, Second European ecological modelling conference, Pula, Croatia, 1999. Abstract.
  
  

Other unpublished work

• I. Bratko, S. Dzeroski, B. Kompare, and W. J. Walley. Analysis of Environmental Data with Machine Learning Methods I. Jozef Stefan Institute, Ljubljana, Slovenia, 1999. Teaching Material.
  
  
• I. Bratko, S. Dzeroski, B. Kompare, and W. J. Walley. Analysis of Environmental Data with Machine Learning Methods II. Jozef Stefan Institute, Ljubljana, Slovenia, 1999. Teaching Material.
  
  
• S. Dzeroski. Data mining and knowledge discovery: Seminar, Bled, May 12-13, 1999. Jozef Stefan Institute, Ljubljana, Slovenia, 1999.
  
  
• S. E. Jorgensen, S. Dzeroski, M. Debeljak, and A. Kobler. Classical and automated ecological modelling. Department of Forestry and Renewable Forest Resources, Biotechnical Faculty, University of Ljubljana, Slovenia, 1999. In Slovenian.
  
  

Book chapter

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

Journal articles

• S. Dzeroski, and T. Erjavec. Inductive learning of multilingual morphology. Electrotechnical Review 65(5): 296-302, 1998.
  
  
full article 807 k



• S. Dzeroski, S. Schulze-Kremer, K. Heidtke, K. Siems, D. Wettschereck, and H. Blockeel. Diterpene structure elucidation from ¹³C NMR spectra with inductive logic programming. Applied Artificial Intelligence, 12: 363-383, 1998.
  
  
full article 331 k



• L. Todorovski, S. Dzeroski, and B. Kompare. Modeling and prediction of phytoplankton growth with equation discovery. Ecological Modelling 113: 71-81, 1998.
  
  
full article 177 k



• B. Zupan, and S. Dzeroski. Acquiring and validating background knowledge for machine learning using function decomposition. Artificial Intelligence in Medicine, 14: 101-117, 1998.
  
  
full article 155 k

Published (conference) papers

• J. Dimec, S. Dzeroski, L. Todorovski, and D. Hristovski. 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, pages 43-48. Jozef Stefan Institute, Ljubljana, Slovenia, 1998. In Slovene.
  
  
full paper link



• S. Dzeroski, L. De Raedt, and H. Blockeel. Relational reinforcement learning. In Proc. Fifteenth International Conference on Machine Learning, pages 136-143. Morgan Kaufmann, San Mateo, CA, 1998. Also in Proc. Eighth International Conference on Inductive Logic Programming, pages 11-22. Springer, Berlin, 1998.
  
  
full paper 174 k



• S. Dzeroski, N. Jacobs, M. Molina, and C. Moure. ILP experiments in detecting traffic problems. In Proc. Tenth European Conference on Machine Learning, pages 61-66. Springer, Berlin, 1998.
  
  
full paper 128 k



• S. Dzeroski, N. Jacobs, M. Molina, C. Moure, S. Muggleton, and W. van Laer. Detecting traffic problems with ILP. In Proc. Eighth International Conference on Inductive Logic Programming, pages 281-290. Springer, Berlin, 1998.
  
  
full paper 266 k



• S. Manandhar, S. Dzeroski, and T. Erjavec. Learning multilingual morphology with CLOG. In Proc. Eighth International Conference on Inductive Logic Programming, pages 135-144. Springer, Berlin, 1998.
  
  
full paper 213 k

Other published work

• P. B. Brazdil, A. Srinivasan, A. Jorge, A. Knobbe, S. Dzeroski, and P. van der Putten. International Summer School on Knowledge Discovery in Databases and Data Mining: Methods and Applications, Volume III. Caminha, Portugal, 1998.
  
  
• M. Debeljak, S. Dzeroski, and M. Adamic. Interactions among the red deer (Cervus elaphus, L.) population, meteorological parameters and new growth of the natural regenerated forest in Sneznik, Slovenia. In Abstracts: 1998 Annual meeting. Baltimore: International Society for Ecological Modelling, 1998, page 6.
  
  
• B. Kompare, L. Todorovski, and S. Dzeroski. Modelling and prediction of phytoplankton growth in a lake using artificial intelligence tools. In Book of abstracts. Dublin: Societas Internationalis Limnologiae, 1998, page 37.
  
  

Other unpublished work

• I. Bratko, S. Dzeroski, and I. Kononenko. Knowledge Discovery in Databases. Teaching materials for a one-day seminar of the Center for knowledge transfer in the area of information technologies. Jozef Stefan Institute, Ljubljana, 1998.
  
  
• I. Bratko, S. Dzeroski, B. Kompare, and W. J. Walley. Analysis of Environmental Data with Machine Learning Methods. Teaching materials for a four-day seminar of the Center for knowledge transfer in the area of information technologies. Two volumes. Jozef Stefan Institute, Ljubljana, 1998.
  
  
• S. Dzeroski, editor. Inductive Logic Programming Tutorial Day. Lecture notes. University of Louisville, KY, 1998.
  
  

Book

• N. Lavrac, and S. Dzeroski, editors. Inductive Logic Programming: Proceedings of the Seventh International Workshop, Prague, Czech Republic, September 1997. Springer, Berlin, 1997. Lecture Notes in Artificial Intelligence, 1297.
  
  
springer link

Book chapters

• S. Dzeroski, S. Schulze-Kremer, K. Heidtke, K. Siems, and D. Wettschereck. Diterpene structure elucidation from ¹³C NMR spectra with machine learning. In N. Lavrac, E. Keravnou, and B. Zupan, editors, Intelligent Data Analysis in Medicine and Pharmacology, pages 207-225. Kluwer, Dordrecht, 1997.
  
  
• N. Lavrac, D. Gamberger, and S. Dzeroski. Noise elimination applied in early diagnosis of rheumatic diseases. In N. Lavrac, E. Keravnou, and B. Zupan, editors, Intelligent Data Analysis in Medicine and Pharmacology, pages 187-205. Kluwer, Dordrecht, 1997.
  
  

Journal articles

• S. Dzeroski, J. Grbovic, W. J. Walley, and B. Kompare. Using machine learning techniques in the construction of models. Part II: Rule induction. Ecological Modelling, 95: 95-111, 1997.
  
  
full article 1.466 k



• B. Kompare, F. Steinman, U. Cerar, and S. Dzeroski. Prediction of rainfall runoff from catchment by data analysis with machine learning tools within artificial intelligence tools. Acta Hydrotechnica, 15/17: 79-94, 1997. In Slovenian.
  
  
full article 9.680 k

Published (conference) papers

• Y. Dimopoulos, S. Dzeroski, and T. Kakas. Integrating explanatory and descriptive learning in ILP. In Proc. Fifteenth International Joint Conference on Artificial Intelligence, pages 900-906. Morgan Kaufmann, San Mateo, CA, 1997.
  
  
full paper 165 k



• S. Dzeroski, D. Demsar, J. Grbovic, and W. J. Walley. Learning to infer chemical parameters of river water quality from bioindicator data. In Proc. Sixth Electrotechnical and Computer Science Conference, Volume B, pages 129-132. Slovenia Section IEEE, Ljubljana, Slovenia, 1997.
  
  
full paper 348 k



• S. Dzeroski, and T. Erjavec Induction of Slovene Nominal Paradigms. In Proc. Seventh International Workshop on Inductive Logic Programming, pages 141-148. Springer, Berlin, 1997.
  
  
• S. Dzeroski, and T. Erjavec. Learning Slovene Declensions with FOIDL. In Fourteenth International Conference on Machine Learning - Workshop Notes on Empirical Learning of Natural Language Processing Tasks, pages 49-60. Laboratory of Intelligent Systems, Faculty of Informatics and Statistics, University of Economics, Prague, Czech Republic, 1997.
  
  
full paper 179 k | full paper link



• S. Dzeroski, J. Grbovic, W. J. Walley, and D. Demsar. 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, pages 331-340. Computational Mechanics Publications, Southampton, 1997.
  
  
• S. Dzeroski, G. Potamias, V. Moustakis, and G. Charissis. Automated revision of expert rules for treating acute abdominal pain in children. In Proc. Sixth European Conference on Artificial Intelligence in Medicine Europe, pages 98-109. Springer, Berlin, 1997.
  
  
full paper 711 k



• B. Kompare, S. Dzeroski, and A. Karalic. Identification of the Lake of Bled ecosystem with the artificial intelligence tools M5 and FORS. In Proc. Fourth International Conference on Water Pollution, pages 789-798. Computational Mechanics Publications, Southampton, 1997.
  
  
• B. Kompare, S. Dzeroski, and V. Krizman. Modelling the growth of algae in the Lagoon of Venice with the artificial intelligence tool GoldHorn. In Proc. Fourth International Conference on Water Pollution, pages 799-808. Computational Mechanics Publications, Southampton, 1997.
  
  
• B. Kontic, and S. Dzeroski. Perspective of machine learning in epidemiological studies. In Proc. International Symposium on Environmental Epidemiology in Central and Eastern Europe, pages 27-30. International Institute for Rural and Environmental Health, Bratislava, Slovakia, 1997.
  
  
full paper 314 k



• L. Todorovski, and S. Dzeroski. Declarative bias in equation discovery. In Proc. Fourteenth International Conference on Machine Learning, pages 376-384. Morgan Kaufmann, San Mateo, CA, 1997.
  
  
full paper 186 k



• L. Todorovski, S. Dzeroski, and B. Kompare. Automated modelling of phytoplankton growth using ecological domain knowledge. In Proc. Fourth International Conference on Water Pollution, pages 533-542. Computational Mechanics Publications, Southampton, 1997.
  
  
full paper 584 k



• W. van Laer, L. De Raedt, and S. Dzeroski. On multi-class problems and discretization in inductive logic programming. In Proc. Tenth International Symposium on Foundations of Intelligent Systems, pages 277-286. Springer, Berlin, 1997.
  
  
full paper 221 k



• B. Zupan, and S. Dzeroski. Acquiring and validating background knowledge for machine learning using function decomposition. In Proc. Sixth European Conference on Artificial Intelligence in Medicine Europe, pages 86-97. Springer, Berlin, 1997.
  
  
full paper 249 k

Other published work

• I. Bratko, S. Dzeroski, and B. Kompare. Analysis of ecological data with machine learning methods - Plan regularities, take into account consequences. Environment, 1/2: 26, 1997. In Slovenian.
  
  
• L. Todorovski, S. Dzeroski, and B. Kompare. Modeling and prediction of phytoplankton growth with equation discovery. In First European ecological modelling conference: Pula, Croatia, September 1997. International society for ecological modelling, 1997, page. 40. Abstract.
  
  

Other unpublished work

• S. Dzeroski, and N. Lavrac, editors. ILP & KDD, International Summer School on Inductive Logic Programming and Knowledge Discovery in Databases, Lecture notes. Czech Technical University, Prague, Czech Republic, 1997.
  
  

Book chapters

• S. Dzeroski. Inductive logic programming and knowledge discovery in databases. In U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, R. Uthurusamy, editors, Advances in Knowledge Discovery and Data Mining, pages 118-152. MIT Press, Cambridge, MA, 1996.
  
  
full chapter 2.264 k



• S. Dzeroski, and I. Bratko. Applications of inductive logic programming. In L. De Raedt, editor, Advances in Inductive Logic Programming, pages 65-81. IOS Press, Amsterdam, 1996.
  
  
full chapter 1.493 k



• N. Lavrac, S. Dzeroski, and I. Bratko. Imperfect data handling in inductive logic programming. In L. De Raedt, editor, Advances in Inductive Logic Programming, pages 48-64. IOS Press, Amsterdam, 1996.
  
  
full chapter 1.345 k

Journal articles

• S. Dzeroski, and N. Lavrac. Rule induction and instance-based learning applied in medical diagnosis. Technology and Health Care, 4: 203-221, 1996.
  
  
full article 1.269 k



• N. Lavrac, D. Zupanic, I. Weber, D. Kazakov, O. Stepankova, and S. Dzeroski. ILPNET repositories on WWW: Inductive Logic Programming systems, datasets and bibliography. AI Communications, 9(4): 157-206, 1996.
  
  
full article 587 k

Published (conference) papers

• S. Dzeroski, S. Schulze-Kremer, K. Heidtke, K. Siems, and D. Wettschereck. Applying ILP to diterpene structure elucidation from ¹³C NMR spectra. In Proc. Sixth International Workshop on Inductive Logic Programming, pages 41-54. Springer, Berlin, 1996.
  
  
full paper 219 k



• D. Gamberger, N. Lavrac, and S. Dzeroski. Noise elimination in inductive concept learning: A case study in medical diagnosis. In Proc. Seventh International Workshop on Algorithmic Learning Theory, pages 199-212. Springer, Berlin, 1996.
  
  
full paper 222 k



• W. J. Walley, and S. Dzeroski. Biological monitoring: A comparison between Bayesian, neural and machine learning methods of water quality classification. In Proc. International Symposium on Environmental Software Systems, 1995, pages 229-240. Chapman and Hall, London, 1996.
  
  
full paper 1.589 k

Unpublished (workshop) papers

• S. Dzeroski, S. Schulze-Kremer, K. Heidtke, K. Siems, and D. Wettschereck. Applying ILP to diterpene structure elucidation from ¹³C NMR spectra. In Proc. Machine Learning Network Workshop on Data Mining with Inductive Logic Programming. Bari, Italy, July 1996.
  
  
full paper 219 k



• S. Dzeroski, S. Schulze-Kremer, K. Heidtke, K. Siems, and D. Wettschereck. Diterpene structure elucidation from ¹³C NMR spectra with machine learning. In Proc. European Conference on Artificial Intelligence Workshop on Intelligent Data Analysis for Medicine and Pharmacology. Budapest, Hungary, August 1996.
  
  
full paper 3.151 k



• N. Lavrac, D. Gamberger, and S. Dzeroski. Noise elimination applied in early diagnosis of rheumatic diseases. In Proc. European Conference on Artificial Intelligence Workshop on Intelligent Data Analysis for Medicine and Pharmacology. Budapest, Hungary, August 1996.
  
  
• W. van Laer, S. Dzeroski, and L. De Raedt. Multi-class problems and discretization in ICL. In Proc. Machine Learning Network Workshop on Data Mining with Inductive Logic Programming, pages 53-60. Bari, Italy, July 1996.
  
  
full paper 180 k

Technical report

• Y. Dimopoulos, S. Dzeroski, and T. Kakas. Integrating explanatory and descriptive learning in ILP. Technical Report TR-96-16, Department of Computer Science, University of Cyprus, Nicosia, Cyprus, 1996.
  
  
full paper 165 k

Other published work

• N. Lavrac, and S. Dzeroski. A reply to Pazzani's book review of "Inductive Logic Programming: Techniques and Applications". Machine Learning, 23: 109-111, 1996.
  
  
full paper 148 k

Other unpublished work

• I. Bratko, S. Dzeroski, and B. Kompare. Analysis of Ecological Data with Machine Learning Methods. Teaching materials for a two-day seminar of the Center for knowledge transfer in the area of information technologies. Jozef Stefan Institute, Ljubljana, 1996.
  
  
• N. Lavrac, I. Weber, D. Zupanic, D. Kazakov, O. Stepankova, and S. Dzeroski. ILPNET repositories on WWW: Inductive logic programming systems, datasets and bibliography: PECO 92. Ljubljana, 1996.
  
  

Book chapter

• S. Dzeroski, S. Muggleton, and S. Russell. PAC-learnability of constrained nonrecursive logic programs. In T. Petsche, S. Judd, and S. Hanson, editors, Computational Learning Theory and Natural Learning Systems, Volume 3, pages 243-255. MIT Press, Cambridge, MA, 1995.
  
  

Journal articles

• I. Bratko, and S. Dzeroski. Engineering applications of inductive logic programming. New Generation Computing, 13: 313-333, (Special issue on Inductive Logic Programming), 1995.
  
  
full article 3.119 k



• S. Dzeroski, and L. Todorovski. Discovering dynamics: From inductive logic programming to machine discovery. Journal of Intelligent Information Systems, 4: 89-108 (Special issue on Knowledge Discovery in Databases), 1995.
  
  
full article 262 k



• V. Krizman, S. Dzeroski, and B. Kompare. Discovering dynamics from measured data. Electrotechnical Review, 62(3-4): 191-198, 1995.
  
  
full article 819 k

Published (conference) papers

• I. Bratko, and S. Dzeroski. New AI techniques applied to modelling. In Proc. Second International Conference Design to Manufacture in Modern Industry, pages 359-372. University of Maribor, 1995.
  
  
• S. Dzeroski. Learning first-order clausal theories in the presence of noise. In Proc. Fifth Scandinavian Conference on Artificial Intelligence, pages 51-60. IOS Press, Amsterdam, 1995.
  
  
• S. Dzeroski, and J. Grbovic. Knowledge discovery in a water quality database. In Proc. First International Conference on Knowledge Discovery and Data Mining, pages 81-86. AAAI Press, Menlo Park, CA, 1995.
  
  
• S. Dzeroski, L. Todorovski, and T. Urbancic. Handling real numbers in ILP: A step towards successful behavioural cloning. In Proc. Eighth European Conference on Machine Learning, pages 283-286. Springer, Berlin, 1995.
  
  
• B. Kompare, and S. Dzeroski. Getting more out of data: Automated modelling of algal growth with machine learning. In Proc. International Conference on Coastal Ocean Space Utilization, pages 209-220, University of Hawaii, 1995.
  
  
• V. Krizman, and S. Dzeroski. Discovering dynamics from measured data. In Proc. Eighth European Conference on Machine Learning, pages 169-174. Springer, Berlin, 1995.
  
  
• S. Wrobel, and S. Dzeroski. The ILP description learning problem: Towards a general model-level definition of data mining in ILP. In Beitrage zum 7. Fachgruppentreffen Machinelles Lernen der GI-Fachgruppe 1.1.3, pages 33-39, University of Dortmund, 1995.
  
  
full paper 265 k

Unpublished (workshop) papers

• S. Dzeroski, L. Todorovski, and I. Petrovski. Dynamical system identification with machine learning. In Proc. Machine Learning Workshop on Genetic Programming: From Theory to Real-World Applications, Lake Tahoe, CA, July 1995.
  
  
• V. Krizman, S. Dzeroski, and B. Kompare. Discovering dynamics from measured data. In Working Notes of the MLnet Workshop on Statistics, Machine Learning and Knowledge Discovery in Databases. Heraklion, Greece, April 1995.
  
  
• N. Lavrac, D. Gamberger, and S. Dzeroski. An approach to dimensionality reduction in learning from deductive databases. In Proc. Fifth International Workshop on Inductive Logic Programming, Leuven, Belgium, September 1995.
  
  

Technical reports

• S. Dzeroski, L. Todorovski, and I. Petrovski. Dynamical system identification with machine learning. Technical Report IJS-DP-7140. Jozef Stefan Institute, Ljubljana, Slovenia, 1995.
  
  
• S. Dzeroski, L. Todorovski, and T. Urbancic. Handling real numbers in ILP: A step towards successful behavioural cloning. Technical Report IJS-DP-7265. Jozef Stefan Institute, Ljubljana, Slovenia, 1995.
  
  
• N. Lavrac, and S. Dzeroski. Inductive logic programming techniques. Technical Report IJS-DP-7139. Jozef Stefan Institute, Ljubljana, Slovenia, 1995.
  
  
• N. Lavrac, S. Dzeroski, and I. Bratko. Advances in imperfect data handling and applications of ILP: Final Report ESPRIT III, project 6020 on ILP. Leuven: Katholieke Universiteit, 1995.
  
  

Other unpublished work

• S. Dzeroski. Numerical constraints and learnability in inductive logic programming. PhD Thesis, Faculty of Electrical Engineering and Computer Science, University of Ljubljana, Slovenia, 1995.
  
  

Authored book

• N. Lavrac, and S. Dzeroski. Inductive Logic Programming: Techniques and Applications. Ellis Horwood, Chichester, 1994.
  
  more | full book 1.682 k
  
  

Journal articles

• L. De Raedt, and S. Dzeroski. First order jk-clausal theories are PAC-learnable. Artificial Intelligence, 70: 375-392, 1994.
  
  
full article 1.942 k



• J. U. Kietz, and S. Dzeroski. Inductive logic programming and learnability. SIGART Bulletin 5(1): 22-32 (Special issue on Inductive Logic Programming), 1994.
  
  
full article 234 k



• B. Kompare, I. Bratko, F. Steinman, and S. Dzeroski. Using machine learning techniques in the construction of models. Part I: Introduction. Ecological Modelling, 75/76: 617-628, 1994.
  
  
full article 774 k



• N. Lavrac, and S. Dzeroski. Weakening the language bias in LINUS. Journal on Experimental and Theoretical Artificial Intelligence 6(1): 95-119 (Special issue on Algorithmic Learning Theory), 1994.
  
  
full article 1.853 k



• L. Todorovski, and S. Dzeroski. Modeling dynamic systems with machine discovery. Electrotechnical Review, 61(1-2): 55-64, 1994. In Slovenian.
  
  
full article 845 k

Published (conference) papers

• S. Dzeroski, L. Dehaspe, B. Ruck, and W. Walley. Classification of river water quality data using machine learning. In P. Zannetti, editor, Computer Techniques in Environmental Studies V (Proc. Fifth International Conference on the Development and Application of Computer Techniques to Environmental Studies), Volume I: Pollution modelling, pages 129-137, Computational Mechanics Publications, Southampton, 1994.
  
  
• S. Dzeroski, J. Grbovic, and D. Lican-Milosevic. Analysis of water quality data with machine learning. In Proc. Third Electrotechnical and Computer Science Conference, Volume B, pages 175-178. Slovenia Section IEEE, Ljubljana, Slovenia, 1994. In Slovenian.
  
  
• S. Dzeroski, and I. Petrovski. Discovering dynamics with genetic programming. In Proc. Seventh European Conference on Machine Learning, pages 347-350. Springer, Berlin, 1994.
  
  
• S. Dzeroski, and L. Todorovski. Handling real numbers in inductive logic programming. In Proc. Third Electrotechnical and Computer Science Conference, Volume B, pages 143-146. Slovenia Section IEEE, Ljubljana, Slovenia, 1994.
  
  
• B. Kompare, and S. Dzeroski. Two artificial intelligence methods for knowledge synthesis from environmental data. In P. Zannetti, editor, Computer Techniques in Environmental Studies V (Proc. Fifth International Conference on the Development and Application of Computer Techniques to Environmental Studies), Volume II: Environmental Systems, pages 265-272, Computational Mechanics Publications, Southampton, 1994.
  
  

Unpublished (workshop) papers

• L. De Raedt, and S. Dzeroski. First order jk-clausal theories are PAC-learnable. In Proc. Fourth International Workshop on Inductive Logic Programming, Bad Honnef/Bonn, Germany, September 1994.
  
  

Technical report

• S. Dzeroski, and I. Petrovski. Discovering dynamics with genetic programming. Technical Report IJS-DP-6945. Jozef Stefan Institute, Ljubljana, Slovenia, 1994.
  
  

Journal articles

• S. Dzeroski, B. Cestnik, and I. Petrovski. Using the m-estimate in rule induction. Journal of Computing and Information Technology, 1(1): 37-46, 1993.
  
  
full article 1.386 k



• S. Dzeroski, and N. Lavrac. Inductive learning in deductive databases. IEEE Transactions on Knowledge and Data Engineering 5(6): 939-949 (Special issue on Learning and Discovery in Knowledge-Based Databases), 1993.
  
  
full article 1.035 k



• N. Lavrac, S. Dzeroski, V. Pirnat, and V. Krizman. The use of background knowledge in learning medical diagnostic rules. Applied Artificial Intelligence, 7(3): 273-293, 1993.
  
  
full article 1.748 k

Published (conference) papers

• L. De Raedt, N. Lavrac, and S. Dzeroski. Multiple predicate learning. In Proc. Thirteenth International Joint Conference on Artificial Intelligence, pages 1037-1042. Morgan Kaufmann, San Mateo, CA, 1993.
  
  
• S. Dzeroski. Handling imperfect data in inductive logic programming. In Proc. Fourth Scandinavian Conference on Artificial Intelligence, pages 111-125. IOS Press, Amsterdam, 1993.
  
  
• S. Dzeroski, and D. Lican. Modeling algal growth in the lagoon of Venice with regression trees. In Proc. Second Electrotechnical and Computer Science Conference, Volume B, pages 205-208. Slovenia Section IEEE, Ljubljana, Slovenia, 1993. In Slovenian.
  
  
• S. Dzeroski, S. Muggleton, and S. Russell. Learnability of constrained logic programs. In Proc. Sixth European Conference on Machine Learning, pages 342-347. Springer, Berlin, 1993.
  
  
• S. Dzeroski, and L. Todorovski. Discovering dynamics. In Proc. Tenth International Conference on Machine Learning, pages 97-103. Morgan Kaufmann, San Mateo, CA, 1993.
  
  
• S. Dzeroski, and L. Todorovski. Modeling dynamic systems with machine discovery. In Proc. Second Electrotechnical and Computer Science Conference, Volume B, pages 209-212. Slovenia Section IEEE, Ljubljana, Slovenia, 1993. In Slovenian.
  
  
full paper 149 k

Unpublished (workshop) papers

• L. De Raedt, N. Lavrac, and S. Dzeroski. Multiple predicate learning. In Proc. Third International Workshop on Inductive Logic Programming, pages 221-240, Bled, Slovenia, March 1993.
  
  
• S. Dzeroski, and L. Todorovski. Discovering dynamics: From inductive logic programming to machine discovery. In Proc. AAAI'93 Workshop on Knowledge Discovery in Databases, pages 125-137, Washington DC, July 1993. Also in Proc. IJCAI'93 Workshop on Inductive Logic Programming, pages 1-13, Chambery, France, August 1993.
  
  
full paper 271 k

Technical reports

• L. De Raedt, N. Lavrac, and S. Dzeroski. Multiple predicate learning. Technical Report KUL-CW-165, Department of Computer Science, Katholieke Universiteit Leuven, Leuven, Belgium, 1993.
  
  
• N. Lavrac, L. De Raedt, and S. Dzeroski. Introduction to inductive machine learning. (Lecture notes for a PhD course in machine learning.) Technical Report IJS-DP-6809. Jozef Stefan Institute, Ljubljana, Slovenia, 1993.
  
  

Other published work

• S. Dzeroski. Report: AAAI'93 (Eleventh National Conference on Artificial Intelligence, Washington DC, July 1993). Informatica 17: 200-201, 1993.
  
  
• S. Dzeroski. Report: ML'93 (Tenth International Conference on Machine Learning, Amherst, MA, June 1993). Informatica 17: 202, 1993.
  
  

Other unpublished work

• N. Lavrac, and S. Dzeroski. Inductive logic programming. Tutorial notes, Fourth Scandinavian Conference on Artificial Intelligence, Stockholm, Sweden, May 1993.
  
  

Book chapters

• S. Dzeroski, and N. Lavrac. Refinement graphs for FOIL and LINUS. In S. H. Muggleton, editor, Inductive Logic Programming, pages 319-333. Academic Press, London, 1992.
  
  
• N. Lavrac, and S. Dzeroski. Inductive learning of relations from noisy examples. In S.H. Muggleton, editor, Inductive Logic Programming, pages 495-516. Academic Press, London, 1992.
  
  

Journal article

• S. Dzeroski. Learning qualitative models with inductive logic programming. Informatica, 16(4): 30-41, 1992.
  
  
full article 2.976 k

Published (conference) papers

• S. Dzeroski, B. Cestnik, and I. Petrovski. The use of Bayesian probability estimates in rule induction. In Proc. First Electrotechnical and Computer Science Conference, Volume B, pages 155-158. Slovenia Section IEEE, Ljubljana, Slovenia, 1992.
  
  
• S. Dzeroski, S. Muggleton, and S. Russell. PAC-learnability of determinate logic programs. In Proc. Fifth ACM Workshop on Computational Learning Theory, pages 128-135, ACM Press, New York, 1992.
  
  
full paper 191 k



• N. Lavrac, and S. Dzeroski. Background knowledge and declarative bias in inductive concept learning. In K. Jantke, editor, Proc. Third International Workshop on Analogical and Inductive Inference, pages 51-71. Springer, Berlin, 1992.
  
  

Unpublished (workshop) papers

• S. Dzeroski, and I. Bratko. Handling noise in inductive logic programming. In Proc. Second International Workshop on Inductive Logic Programming, Tokyo, June 1992.
  
  
• S. Dzeroski, and I. Bratko. Using the m-estimate in inductive logic programming. In Proc. International Workshop on Logical Approaches to Machine Learning, Vienna, August 1992. Also in Proc. First Compulog Net Workshop on Logic Programming in Artificial Intelligence, London, March 1992.
  
  
• S. Dzeroski, and B. Dolsak. Comparison of ILP systems on the problem of finite element mesh design. In Proc. Sixth ISSEK Scientific Workshop. Bled, Slovenia, September 1992.
  
  
• S. Dzeroski, S. Muggleton, and S. Russell. PAC-learnability of constrained nonrecursive logic programs. In Proc. Third International Workshop on Computational Learning Theory and Natural Learning Systems. Wisconsin, Madison, August 1992.
  
  
• N. Lavrac, B. Cestnik, and S. Dzeroski. Search heuristics in empirical inductive logic programming. In Proc. International Workshop on Logical Approaches to Machine Learning, Vienna, August 1992.
  
  
• N. Lavrac, B. Cestnik, and S. Dzeroski. Use of heuristics in empirical inductive logic programming. In Proc. Second International Workshop on Inductive Logic Programming. Tokyo, June 1992.
  
  

Technical report

• S. Dzeroski, B. Cestnik, and I. Petrovski. The use of Bayesian probability estimates in rule induction. Technical Report TIRM-92-051, The Turing Institute, Glasgow, Scotland, 1992.
  
  

Published (conference) papers

• S. Dzeroski, and B. Dolsak. A comparison of relation learning algorithms on the problem of finite element mesh design. In Proc. XXVI Yugoslav Conference of the Society for ETAN, pages 313-320, Ohrid, Macedonia, 1991. In Slovenian.
  
  
• S. Dzeroski, and N. Lavrac. Learning relations from noisy examples: An empirical comparison of LINUS and FOIL. In Proc. Eighth International Workshop on Machine Learning, pages 399-402. Morgan Kaufmann, San Mateo, CA, 1991.
  
  
• N. Lavrac, S. Dzeroski, and M. Grobelnik. Learning nonrecursive definitions of relations with LINUS. In Proc. Fifth European Working Session on Learning, pages 265-281. Springer, Berlin, 1991.
  
  
• N. Lavrac, S. Dzeroski, V. Pirnat, and V. Krizman. Learning rules for early diagnosis of rheumatic diseases. In Proc. Third Scandinavian Conference on Artificial Intelligence, pages 138-149. IOS Press, Amsterdam, 1991.
  
  

Unpublished (workshop) paper

• N. Lavrac, and S. Dzeroski. Inductive learning of relational descriptions from noisy examples. In Proc. International Workshop on Inductive Logic Programming, Vianna do Castello, Portugal, March 1991.
  
  

Technical reports

• S. Dzeroski. mFOIL on the monk's problems. In S. B. Thrun, editor, The monk's problems: A performance comparison of different learning algorithms. Technical report CMU-CS-91-197, Carnegie Mellon University, Pittsburgh, PA, 1991.
  
  
• S. Dzeroski, and N. Lavrac. Learning relations from imperfect data. Technical Report IJS-DP-6163. Jozef Stefan Institute, Ljubljana, Slovenia, 1991.
  
  

Other unpublished work

• S. Dzeroski. Handling noise in inductive logic programming. MSc Thesis, Faculty of Electrical Engineering and Computer Science, University of Ljubljana, Slovenia, 1991.
  
  

Unpublished (workshop) paper

• N. Lavrac, S. Dzeroski, and M. Grobelnik. Experiments in learning nonrecursive definitions of relations with LINUS. In Proc. Fifth ISSEK Scientific Workshop. Udine, Italy, October 1990.
  
  

Technical reports

• S. Dzeroski, and N. Lavrac. Refinement graphs for FOIL and LINUS. Technical Report IJS-DP-5958. Jozef Stefan Institute, Ljubljana, Slovenia, 1990.
  
  
• N. Lavrac, S. Dzeroski, and M. Grobelnik Experiments in learning nonrecursive definitions of relations with LINUS. Technical Report IJS-DP-5863. Jozef Stefan Institute, Ljubljana, Slovenia, 1990.
  
  
• N. Lavrac, S. Dzeroski, and V. Pirnat. Learning rules for early diagnosis of rheumatic diseases. Technical Report IJS-DP-5979. Jozef Stefan Institute, Ljubljana, Slovenia, 1990.
  
  

Unpublished (workshop) paper

• S. Dzeroski, R. Zupanc, and I. Bratko. Pole balancing: Some experiments and creating a new simulation software environment. In Proc. Fourth ISSEK Scientific Workshop. Udine, Italy, September 1989.
  
  

Other unpublished work

• S. Dzeroski. Controlling the inverted pendulum. BSc Thesis, Faculty of Electrical Engineering and Computer Science, University of Ljubljana, Slovenia, 1989. In Slovenian.