ILPnet2 library: S. Dzeroski

ILP publications by S. Dzeroski

This is a list of all publications in the ILPnet2 on-line library which are (co-)authored by S. Dzeroski. The title of the article is a link to the full reference, including -- if provided by the author -- abstract and URL. It also allows easy access to related publications.

2002

H. Blockeel, M. Bruynooghe, S. Dzeroski, J. Ramon, and J. Struyf. Hierarchical Multi-Classification. In Saso Dzeroski, Luc De Raedt, and Stefan Wrobel, editors, Proceedings of the First SIGKDD Workshop on Multi-Relational Data Mining (MRDM-2002), pages 21--35. University of Alberta, Edmonton, Canada, July 2002. More behind this link.

2001

Saso Dzeroski. Data Mining in a Nutshell. In Saso Dzeroski and Nada Lavrac, editors, Relational Data Mining, pages 3--28. Springer-Verlag, September 2001. More behind this link.
Saso Dzeroski and Nada Lavrac. Introduction to Inductive Logic Programming. In Saso Dzeroski and Nada Lavrac, editors, Relational Data Mining, pages 48--73. Springer-Verlag, September 2001. More behind this link.
Saso Dzeroski. Relational Data Mining Applications: An Overview. In Saso Dzeroski and Nada Lavrac, editors, Relational Data Mining, pages 339--364. Springer-Verlag, September 2001. More behind this link.
Saso Dzeroski and Nada Lavrac, editors. Relational Data Mining. Springer-Verlag, Berlin, September 2001. More behind this link.
Ljupco Todorovski, Irene Weber, Nada Lavrac, Olga Stepankova, Saso Dzeroski, Dimitar Kazakov, Darko Zupanic, and Peter Flach. Internet Resources on ILP for KDD. In Saso Dzeroski and Nada Lavrac, editors, Relational Data Mining, pages 375--388. Springer-Verlag, September 2001. More behind this link.
Peter Flach and Saso Dzeroski. Editorial: Inductive Logic Programming is Coming of Age. Machine Learning, 43(3):207--209, September 2001.
Saso Dzeroski, Luc De Raedt, and Kurt Driessens. Relational Reinforcement Learning. Machine Learning, 43(1/2):5--52, April 2001.

2000

James Cussens and Saso Dzeroski, editors. Learning Language in Logic, volume 1925 of Lecture Notes in Computer Science. Springer-Verlag, June 2000. More behind this link.
Saso Dzeroski and Tomaz Erjavec. Learning to Lemmatise Slovene Words. In James Cussens and Saso Dzeroski, editors, Learning Language in Logic, volume 1925 of Lecture Notes in Computer Science, pages 69--88. Springer-Verlag, June 2000. More behind this link.
Saso Dzeroski, James Cussens, and Suresh Manandhar. An Introduction to Inductive Logic Programming and Learning Language in Logic. In James Cussens and Saso Dzeroski, editors, Learning Language in Logic, volume 1925 of Lecture Notes in Computer Science, pages 3--35. Springer-Verlag, June 2000. More behind this link.

1999

Hendrik Blockeel, Saso Dzeroski, and Jasna Grbovic. Simultaneous prediction of multiple chemical parameters of river water quality with TILDE.. In J. Zytkow and J. Rauch, editors, Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery, volume 1704 of Lecture Notes in Artificial Intelligence, pages 32--40. Springer, September 1999.
L. Todorovski and S. Dzeroski. Experiments in meta-level learning with ILP. In J. M. Zytkow and J. Rauch, editors, Proceedings of third European Conference on Principles of data mining and knowledge discovery (PKDD-99), volume 1704 of Lecture Notes in Artificial Intelligence, pages 98--106. Springer-Verlag, September 1999. More behind this link.
J. Cussens, S. Dzeroski, and T. Erjavec. Morphosyntactic Tagging of {S}lovene Using {P}rogol. In S. Dzeroski and P. Flach, editors, Proceedings of the 9th International Workshop on Inductive Logic Programming, volume 1634 of Lecture Notes in Artificial Intelligence, pages 68--79. Springer-Verlag, 1999.
S. Dzeroski, H. Blockeel, B. Kompare, S. Kramer, B. Pfahringer, and W. Van Laer. Experiments in Predicting Biodegradability. In S. Dzeroski and P. Flach, editors, Proceedings of the 9th International Workshop on Inductive Logic Programming, volume 1634 of Lecture Notes in Artificial Intelligence, pages 80--91. Springer-Verlag, 1999.

1998

S. Dzeroski, Nico Jacobs, M. Molina, and C. Moure. ILP experiments in detecting traffic problems. In 10th European Conference on Machine Learning, Lecture Notes in Artificial Intelligence, pages 61--66. Springer-Verlag, August 1998.
S. Dzeroski, N. Jacobs, M. Molina, C. Moure, S. Muggleton, and W. Van Laer. Detecting Traffic Problems with ILP. In D. Page, editor, Proceedings of the 8th International Conference on Inductive Logic Programming, volume 1446 of Lecture Notes in Artificial Intelligence, pages 281--290. Springer-Verlag, 1998. More behind this link.
S. Dzeroski, L. De Raedt, and H. Blockeel. Relational Reinforcement Learning. In D. Page, editor, Proceedings of the 8th International Conference on Inductive Logic Programming, volume 1446 of Lecture Notes in Artificial Intelligence, pages 11--22. Springer-Verlag, 1998.
S. Manandhar, S. Dzeroski, and T. Erjavec. Learning Multilingual Morphology with CLOG. In D. Page, editor, Proceedings of the 8th International Conference on Inductive Logic Programming, volume 1446 of Lecture Notes in Artificial Intelligence, pages 135--144. Springer-Verlag, 1998.
Saso Dzeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, Karsten Siems, Dietrich Wettschereck, and Hendrik Blockeel. Diterpene Structure Elucidation from $^13$C NMR Spectra with Inductive Logic Programming. Applied Artificial Intelligence, 12(5):363--383, July-August 1998. Special Issue on First-Order Knowledge Discovery in Databases

1997

S. Dzeroski and T. Erjavec. Induction of Slovene Nominal Paradigms. In S. Dzeroski and N. Lavrac, editors, Proceedings of the 7th International Workshop on Inductive Logic Programming, volume 1297 of Lecture Notes in Artificial Intelligence, pages 141--148. Springer-Verlag, 1997.

1996

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, 1996.
S. Dzeroski, S. Schulze-Kremer, K.R. Heidtke, K. Siems, and D. Wettschereck. Applying ILP to Diterpene Structure Elucidation from $^13$C NMR Spectra. In S. Muggleton, editor, Proceedings of the 6th International Workshop on Inductive Logic Programming, volume 1314 of Lecture Notes in Artificial Intelligence, pages 41--54. Springer-Verlag, 1996.
S. Dzeroski, S. Schulze-Kremer, K.R. Heidtke, K. Siems, and D. Wettschereck. Applying ILP to Diterpene Structure Elucidation from $^13$C NMR Spectra. In Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programing, pages 12--24, 1996.
W. Van Laer, S. Dzeroski, and L. De Raedt. Multi-class problems and discretization in ICL. In Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programing, pages 53--60, 1996.
N. Lavrac, S. Dzeroski, and I. Bratko. Handling Imperfect Data in Inductive Logic Programming. In L. De Raedt, editor, Advances in Inductive Logic Programming, pages 48--64. IOS Press, 1996.

1995

I. Bratko and S. Dzeroski. Engineering applications of ILP. New Generation Computing, Special issue on Inductive Logic Programming, 13(3-4):313--333, 1995.
S. Dzeroski. 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. The MIT Press, 1995.
S. Dzeroski. Numerical constraints and learnability in inductive logic programming. PhD thesis, Faculty of Electrical Engineering and Computer Science, University of Ljubljana, Ljubljana, Slovenia, 1995.
S. Dzeroski. Learning first-order clausal theories in the presence of noise. In A. Aamodt and J. Komorowski, editors, Proceedings of the 5th Scandinavian Conference on Artificial Intelligence, pages 51--60. IOS, Amsterdam, 1995.
S. Dzeroski, L. Dehaspe, B. Ruck, and W. Walley. Classification of river water quality data using machine learning. In Proceedings of the 5th International Conference on the Development and Application of Computer Techniques to Environmental Studies, 1995.
S. Dzeroski and L. Todorovski. Discovering dynamics: From inductive logic programming to machine discovery. Journal of Intelligent Information Systems, 4:89--108, 1995.
S. Dzeroski, L. Todorovski, and T. Urbancic. Handling real numbers in inductive logic programming: A step towards better behavioural clones. In N. Lavrac and S. Wrobel, editors, Proceedings of the 8th European Conference on Machine Learning, volume 912 of Lecture Notes in Artificial Intelligence, pages 283--286. Springer-Verlag, 1995.
N. Lavrac, D. Gamberger, and S. Dzeroski. An approach to Dimensionality Reduction in Learning from Deductive Databases. In L. De Raedt, editor, Proceedings of the 5th International Workshop on Inductive Logic Programming, pages 337--354. Department of Computer Science, Katholieke Universiteit Leuven, 1995.

1994

S. Dzeroski and L. Todorovski. Handling real numbers in inductive logic programming. In Proceedings of the 3rd Electrotechnical and Computer Science Conference, volume B, pages 143--146. Slovenian Section IEEE, Ljubljana, 1994.
J-U. Kietz and S. Dzeroski. Inductive logic programming and learnability. SIGART Bulletin, 5(1):22--32, 1994.
N. Lavrac and S. Dzeroski. Weakening the language bias in LINUS. Journal of Experimental and Theoretical Artificial Intelligence, 6(1):95--119, 1994.
N. Lavrac and S. Dzeroski. Inductive Logic Programming: Techniques and Applications. Ellis Horwood, 1994.
L. De Raedt and S. Dzeroski. First Order $jk$-Clausal Theories are PAC-Learnable. Artificial Intelligence, 70:375--392, 1994.
L. De Raedt and S. Dzeroski. First-order jk-clausal Theories are PAC-Learnable. In S. Wrobel, editor, Proceedings of the 4th International Workshop on Inductive Logic Programming, volume 237 of GMD-Studien, pages 49--50. Gesellschaft für Mathematik und Datenverarbeitung MBH, 1994. (Abstract)

1993

S. Dzeroski. Handling imperfect data in inductive logic programming. In Proceedings of the 4th Scandinavian Conference on Artificial Intelligence, pages 111--125. IOS Press, 1993.
S. Dzeroski and N. Lavrac. Inductive learning in deductive databases. IEEE Transactions on Knowledge and Data Engineering, 5(6):939--949, 1993.
S. Dzeroski, S. Muggleton, and S. Russell. Learnability of constrained logic programs. In P. Brazdil, editor, Proceedings of the 6th European Conference on Machine Learning, volume 667 of Lecture Notes in Artificial Intelligence, pages 342--347. Springer-Verlag, 1993.
S. Dzeroski and L. Todorovski. Discovering dynamics. In Proceedings of the AAAI-93 Workshop on Knowledge Discovery in Databases, pages 125--137. AAAI Press, 1993.
S. Dzeroski and L. Todorovski. Discovering dynamics: From inductive logic programming to machine discovery. In Proceedings of the 10th International Conference on Machine Learning, pages 97--103. Morgan Kaufmann, 1993.
S. Dzeroski and L. Todorovski. Discovery Dynamics: From Inductive Logic Programming to Machine Discovery. In F. Bergadano, L. De Raedt, S. Matwin, and S. Muggleton, editors, Proceedings of the IJCAI-93 Workshop on Inductive Logic Programming, pages 1--13. Morgan Kaufmann, 1993.
N. Lavrac, S. Dzeroski, V. Pirnat, and V. Krizman. The utility of background knowledge in learning medical diagnostic rules. Applied Artificial Intelligence, 7:273--293, 1993.
L. De Raedt, N. Lavrac, and S. Dzeroski. Multiple Predicate Learning. In R. Bajcsy, editor, Proceedings of the 13th International Joint Conference on Artificial Intelligence, pages 1037--1043. Morgan Kaufmann, 1993.
L. De Raedt, N. Lavrac, and S. Dzeroski. Multiple predicate learning. In S. Muggleton, editor, Proceedings of the 3rd International Workshop on Inductive Logic Programming, pages 221--240. J. Stefan Institute, 1993.

1992

S. Dzeroski. Learning qualitative models with inductive logic programming. Informatica, 16(4):30--41, 1992.
S. Dzeroski and I. Bratko. Using the $m$-estimate in inductive logic programming. In C. Rouveirol, editor, Proceedings of the ECAI-92 Workshop on Logical Approaches to Machine Learning, 1992.
S. Dzeroski and I. Bratko. Handling noise in Inductive Logic Programming. In S. Muggleton, editor, Proceedings of the 2nd International Workshop on Inductive Logic Programming, Report ICOT TM-1182, 1992.
S. Dzeroski and B. Dolsak. Comparison of ILP systems on the problem of finite element mesh design. In Proceedings of the 6th International School for the Synthesis of Expert Knowledge, 1992.
S. Dzeroski and N. Lavrac. Refinement Graphs for FOIL and LINUS. In S. Muggleton, editor, Inductive Logic Programming, pages 319--334. Academic Press, 1992.
S. Dzeroski, S. Muggleton, and S. Russell. PAC-learnability of determinate logic programs. In Proceedings of the 5th ACM Workshop on Computational Learning Theory, pages 128--135. ACM Press, 1992.
S. Dzeroski, S. Muggleton, and S. Russell. PAC-learnability of constrained nonrecursive logic programs. In Proceedings of the 3rd International Workshop on Computational Learning Theory and Natural Learning Systems, 1992.
N. Lavrac, B. Cestnik, and S. Dzeroski. Search heuristics in empirical inductive logic programming. In C. Rouveirol, editor, Proceedings of the ECAI-92 Workshop on Logical Approaches to Machine Learning, 1992.
N. Lavrac, B. Cestnik, and S. Dzeroski. Use of heuristics in empirical inductive logic programming. In S. Muggleton, editor, Proceedings of the 2nd International Workshop on Inductive Logic Programming, Report ICOT TM-1182, 1992.
N. Lavrac and S. Dzeroski. Inductive Learning of Relations from Noisy Examples. In S. Muggleton, editor, Inductive Logic Programming, pages 495--516. Academic Press, 1992.
N. Lavrac and S. Dzeroski. Background knowledge and declarative bias in inductive concept learning. In K. Jantke, editor, Proceedings 3rd International Workshop on Analogical and Inductive Inference, pages 51--71. Springer-Verlag, 1992. (Invited paper)

1991

S. Dzeroski. Handling noise in inductive logic programming. Master's thesis, Faculty of Electrical Engineering and Computer Science, University of Ljubljana, 1991.
S. Dzeroski and B. Dolsak. A comparison of relation learning algorithms on the problem of finite element mesh design. In Proceedings of the 26th Yugoslav Conference of the Society for ETAN, 1991. In Slovenian
S. Dzeroski and N. Lavrac. Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL. In L. Birnbaum and G. Collins, editors, Proceedings of the 8th International Workshop on Machine Learning, pages 399--402. Morgan Kaufmann, 1991.
S. Dzeroski and N. Lavrac. Learning relations from imperfect data. Technical Report IJS-DP-6163, Jo\v zef Stefan Institute, 1991.
N. Lavrac and S. Dzeroski. Inductive Learning of Relational Descriptions from Noisy Examples. In S. Muggleton, editor, Proceedings of the 1st International Workshop on Inductive Logic Programming, pages 259--278, 1991.
N. Lavrac, S. Dzeroski, and M. Grobelnik. Learning Nonrecursive Definitions of Relations with LINUS. In Y. Kodratoff, editor, Proceedings of the 5th European Working Session on Learning, volume 482 of Lecture Notes in Artificial Intelligence, pages 265--281. Springer-Verlag, 1991.
N. Lavrac, S. Dzeroski, V. Pirnat, and [[V. Kri\v zman]]. Learning rules for early diagnosis of rheumatic diseases. In Proceedings of the 3rd Scandinavian Conference on Artificial Intelligence, pages 138--149. IOS Press, 1991.