Scientific publications of Jan Struyf

Articles in international reviewed journals

  1. S. Dzeroski, and J. Struyf, 5th international workshop on knowledge discovery in inductive databases (KDID2006): Workshop report, SIGKDD Explorations - Newsletter of the ACM Special Interest Group on Knowledge Discovery and Data Mining 9 (1), pp. 56-58, June, 2007.
  2. D. Demsar, S. Dzeroski, T. Larsen, J. Struyf, J. Axelsen, M. Bruus Pedersen, and P. Henning Krogh, Using multi-objective classification to model communities of soil microarthropods, Ecological Modelling 191 (1), pp. 131-143, 2006.
  3. J. Struyf, J. Ramon, M. Bruynooghe, S. Verbaeten, and H. Blockeel, Compact representation of knowledge bases in inductive logic programming, Mach. Learn. 57 (3), pp. 305-333, December, 2004.
  4. V. Santos Costa, A. Srinivasan, R. Camacho, H. Blockeel, B. Demoen, G. Janssens, J. Struyf, H. Vandecasteele, and W. Van Laer, Query transformations for improving the efficiency of ILP systems, Journal of Machine Learning Research 4 (Aug), pp. 465-491, August, 2003.
  5. H. Blockeel, and J. Struyf, Efficient algorithms for decision tree cross-validation, Journal of Machine Learning Research 3 (Dec), pp. 621-650, 2002.
  6. H. Blockeel, and J. Struyf, Deriving biased classifiers for better ROC performance, Informatica 26 (1), pp. 77-84, May, 2002.

Articles in other scientific journals

  1. J. Struyf, Techniques for improving the efficiency of inductive logic programming in the context of data mining, BNVKI Newsletter 22 (1), pp. 10-12, February, 2005.

Contributions at international conferences, published in proceedings

  1. J. Struyf, and S. Dzeroski, Clustering trees with instance level constraints, Machine Learning: ECML 2007, 18th European conference on Machine Learning, Proceedings (Kok, J.N. and Koronacki, J. and Lopez de Mantaras, R. and Matwin, S. and Mladenic, D. and Skowron, A., eds.), vol 4701, Lecture Notes in Computer Science, pp. 359-370, 2007
  2. W. Meert, J. Struyf, and H. Blockeel, Learning ground CP-logic theories by means by Bayesian network techniques, Proceedings of the 6th International Workshop on Multi-Relational Data Mining (Malerba, D. and Appice, A. and Ceci, M., eds.), pp. 93-104, 2007
  3. D. Kocev, C. Vens, J. Struyf, and S. Dzeroski, Ensembles of multi-objective decision trees, Machine Learning: ECML 2007, 18th European Conference on Machine Learning, Proceedings (Kok, J. N. and Koronacki, J. and Lopez de Mantaras, R. and Matwin, S. and Mladenic, D. and Skowron, A., eds.), vol 4701, Lecture Notes in Computer Science, pp. 624-631, 2007
  4. D. Kocev, J. Struyf, and S. Dzeroski, Beam search induction and similarity constraints for predictive clustering trees, Knowledge Discovery in Inductive Databases, 5th International Workshop, KDID 2006, Berlin, Germany, September 18, 2006, Revised Selected and Invited Papers (Dzeroski, S. and Struyf, J., eds.), vol 4747, Lecture Notes in Computer Science, pp. 134-151, 2007
  5. E. Fromont, H. Blockeel, and J. Struyf, Integrating decision tree learning into inductive databases, Knowledge Discovery in Inductive Databases, 5th International Workshop, KDID 2006, Berlin, Germany, September 18, 2006, Revised Selected and Invited Papers (Dzeroski, S. and Struyf, J., eds.), vol 4747, Lecture Notes in Computer Science, pp. 81-96, 2007
  6. S. Dzeroski, V. Gjorgjioski, I. Slavkov, and J. Struyf, Analysis of time series data with predictive clustering trees, Knowledge Discovery in Inductive Databases, 5th International Workshop, KDID 2006, Berlin, Germany, September 18, 2006, Revised Selected and Invited Papers (Dzeroski, S. and Struyf, J., eds.), vol 4747, Lecture Notes in Computer Science, pp. 63-80, 2007
  7. J. Davis, I. Ong, J. Struyf, E. Burnside, D. Page, and V. Santos Costa, Change of representation for statistical relational learning, IJCAI 2007, Proceedings of the 20th International Joint Conference on Artificial Intelligence (Veloso, M., ed.), pp. 2719-2726, 2007
  8. B. Zenko, S. Dzeroski, and J. Struyf, Learning predictive clustering rules, Knowledge Discovery in Inductive Databases, 4th International Workshop, KDID'05, Revised, Selected and Invited Papers (Bonchi, F. and Boulicaut, J.-F., eds.), vol 3933, Lecture Notes in Computer Science, pp. 234-250, 2006
  9. J. Struyf, and S. Dzeroski, Constraint based induction of multi-objective regression trees, Knowledge Discovery in Inductive Databases, 4th International Workshop, KDID'05, Revised, Selected and Inductive Papers (Bonchi, F. and Boulicaut, J.-F., eds.), vol 3933, Lecture Notes in Computer Science, pp. 222-233, 2006
  10. J. Struyf, J. Davis, and D. Page, An efficient approximation to lookahead in relational learners, Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Proceedings (Fürnkranz, J. and Scheffer, T. and Spiliopoulou, M., eds.), vol 4212, Lecture Notes in Artificial Intelligence, pp. 775-782, 2006
  11. D. Kocev, S. Dzeroski, and J. Struyf, Similarity constraints in beam-search induction of predictive clustering trees, Proceedings of the Conference on Data Mining and Data Warehouses (SiKDD 2006) at the 9th International Multi-conference on Information Society (IS 2006) (Grobelnik, M. and Mladenic, D., eds.), pp. 267-270, 2006
  12. S. Dzeroski, I. Slavkov, V. Gjorgjioski, and J. Struyf, Analysis of time series data with predictive clustering trees, Proceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases (Dzeroski, S. and Struyf, J., eds.), pp. 47-58, 2006
  13. H. Blockeel, L. Schietgat, J. Struyf, A. Clare, and S. Dzeroski, Hierarchical multilabel classification trees for gene function prediction (Extended abstract), Probabilistic Modeling and Machine Learning in Structural and Systems Biology (Rousu, J. and Kaski, S. and Ukkonen, E., eds.), pp. 9-14, 2006
  14. H. Blockeel, L. Schietgat, J. Struyf, S. Dzeroski, and A. Clare, Decision trees for hierarchical multilabel classification: A case study in functional genomics, Knowledge Discovery in Databases:PKDD 2006, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Proceedings (Fuernkranz, J. and Scheffer, T. and Spiliopoulou, M., eds.), vol 4213, Lecture Notes in Artificial Intelligence, pp. 18-29, 2006
  15. B. Zenko, S. Dzeroski, and J. Struyf, Learning predictive clustering rules, Proceedings of the 4th International Workshop on Knowledge Discovery in Inductive Databases (KDID 2005) (Bonchi, F. and Boulicaut, J., eds.), pp. 122-133, 2005
  16. J. Struyf, C. Vens, T. Croonenborghs, S. Dzeroski, and H. Blockeel, Applying predictive clustering trees to the inductive logic programming 2005 challenge data, Inductive Logic Programming, 15th International Conference, ILP 2005, Late-Breaking Papers (Kramer, S. and Pfahringer, B., eds.), pp. 111-116, 2005
  17. J. Struyf, and S. Dzeroski, Constraint based induction of multi-objective regression trees, Proceedings of the 4th International Workshop on Knowledge Discovery in Inductive Databases (KDID 2005) (Bonchi, F. and Boulicaut, J., eds.), pp. 110-121, 2005
  18. J. Struyf, S. Dzeroski, H. Blockeel, and A. Clare, Hierarchical multi-classification with predictive clustering trees in functional genomics, Progress in Artificial Intelligence: 12th Portugese Conference on Artificial Intelligence, EPIA 2005, Proceedings (Bento, C. and Cardoso, A. and Dias, G., eds.), vol 3808, Lecture Notes in Computer Science, pp. 272-283, 2005
  19. I. Slavkov, S. Dzeroski, J. Struyf, and S. Loskovska, Constrained clustering of gene expression profiles, Proceedings of the Conference on Data Mining and Data Warehouses (SiKDD 2005) at the 7th International Multi-conference on Information Society 2005 (Grobelnik, M. and Mladenic, D., eds.), pp. 212-215, 2005
  20. D. Kocev, S. Dzeroski, J. Struyf, and S. Loskovska, (Inductive) Quering environment for predictive clustering trees, Proceedings of the 2nd Balkan Conference in Informatics (Kon-Popovska, M. and Zdravkova, K. and Gusev, M., eds.), pp. 193-200, 2005
  21. J. Ramon, and J. Struyf, Efficient theta-subsumption of sets of patterns, Benelearn 2004 - Annual Machine Learning Conference of Belgium and the Netherlands (Nowé, A. and Lenaerts, T. and Steenhaut, K., eds.), pp. 95-102, 2004
  22. A. Van Assche, D. Krzywania, J. Vaneyghen, J. Struyf, and H. Blockeel, First order alternating decision trees, Inductive Logic Programming, 13th International Conference, ILP 2003, Szeged, Hungary, Short Presentations (Horvath, T. and Yamamoto, A., eds.), pp. 116-125, 2003
  23. A. Van Assche, S. Verbaeten, D. Krzywania, J. Struyf, and H. Blockeel, Attribute-value and first order data mining within the STULONG project, Proceedings of the ECML/PKDD - 2003 Workshop on Discovery Challenge (Berka, P. and Rauch, J. and Tsumoto, S., eds.), pp. 108-119, 2003
  24. R. Tronçon, H. Vandecasteele, J. Struyf, B. Demoen, and G. Janssens, Query optimization: Combining query packs and the once-tranformation, Inductive Logic Programming, 13th International Conference, ILP 2003, Szeged, Hungary, Short Presentations (Horvath, T. and Yamamoto, A., eds.), pp. 105-115, 2003
  25. J. Struyf, and H. Blockeel, Query optimization in Inductive Logic Programming by reordering literals, Inductive Logic Programming, 13th International Conference, ILP 2003, Proceedings (Horvath, T. and Yamamoto, A., eds.), vol 2835, Lecture Notes in Computer Science, pp. 329-346, 2003
  26. J. Struyf, J. Ramon, and H. Blockeel, Compact representation of knowledge bases in ILP, Inductive Logic Programming, 12th International Conference, ILP 2002, Revised Papers (Matwin, S. and Sammut, C., eds.), vol 2583, Lecture Notes in Computer Science, pp. 254-269, 2003
  27. J. Ramon, and J. Struyf, Computer science in issues in Baduk, Proceedings of the 2nd International Conference on Baduk (Chihyung, N., ed.), pp. 163-182, 2003
  28. H. Blockeel, M. Bruynooghe, S. Dzeroski, J. Ramon, and J. Struyf, Hierarchical multi-classification, KDD-2002 Workshop Notes: MRDM 2002, Workshop on Multi-Relational Data Mining (De Raedt, L. and Dzeroski, S. and Wrobel, S., eds.), pp. 21-35, 2002
  29. J. Struyf, and H. Blockeel, Efficient cross-validation in ILP, Proceedings of ILP2001 - Eleventh International Conference on Inductive Logic Programming (Rouveirol, C. and Sebag, M., eds.), vol 2157, Lecture Notes in Artificial Intelligence, pp. 228-239, 2001
  30. J. Struyf, and H. Blockeel, Efficient multi-relational data mining, Proceedings of the Eleventh Belgian-Dutch Conference on Machine Learning (Hoste, V. and De Pauw, G., eds.), pp. 69-75, 2001
  31. H. Blockeel, and J. Struyf, Frankenstein classifiers: some experiments on the Sisyphus data set, Proceedings of IDDM-2001 - ECML/PKDD Workshop on Integrating Aspects of Data Mining, Decision Support and Meta-Learning (Giraud-Carrier, C. and Lavrac, N. and Moyle, S., eds.), pp. 1-12, 2001
  32. H. Blockeel, K. Driessens, N. Jacobs, R. Kosala, S. Raeymaekers, J. Ramon, J. Struyf, W. Van Laer, and S. Verbaeten, First order models for the predictive toxicology challenge, ECML/PKDD Workshop : The Predictive Toxicology Challenge 2000-2001 (Helma, C. and King, R. and Kramer, S. and Srinivasan, A., eds.), pp. 1-12, 2001
  33. H. Blockeel, and J. Struyf, Frankenstein classifiers: Some experiments, Proceedings of the Eleventh Belgian-Dutch Conference on Machine Learning (Hoste, V. and De Pauw, G., eds.), pp. 5-12, 2001
  34. H. Blockeel, and J. Struyf, Efficient algorithms for decision tree cross-validation, Proceedings of the Eighteenth International Conference on Machine Learning (Brodley, C. and Danyluk, A., eds.), pp. 11-18, 2001
  35. H. Blockeel, and J. Struyf, Deriving biased classifiers for better ROC performance, Information Society 2001 (Grobelnik, Marko and Mladenic, Dunja, eds.), pp. 124-127, 2001

Contributions at international conferences, not published or only as abstract

  1. J. Struyf, and S. Dzeroski, Clustering trees with instance level constraints (Extended abstract), 19th Belgian-Dutch Conference on Artificial Intelligence, BNAIC 2007, Utrecht, The Netherlands, November 5-6, 2007
  2. S. Dzeroski, V. Gjorgjioski, I. Slavkov, and J. Struyf, Analysis of time series data with predictive clustering trees, Former Freiburg, Leuven and Friends Workshop on Machine Learning, FLF-07, Massembre (Heer), Belgium, March 21-23, 2007
  3. H. Blockeel, L. Schietgat, J. Struyf, S. Dzeroski, and A. Clare, Decision trees for hierarchical multilabel classification: a case study in functional genomics, 7th "Freiburg, Leuven and Friends" Workshop on Machine Learning, FLF-06, Titisee, Germany, March 13-14, 2006
  4. H. Blockeel, L. Schietgat, J. Struyf, S. Dzeroski, and A. Clare, Decision trees for hierarchical multilabel classification: a case study in functional genomics, Joint APrIL/IQ Workshop, Titisee, Germany, March 15-18, 2006
  5. H. Blockeel, L. Schietgat, J. Struyf, S. Dzeroski, and A. Clare, Decision trees for hierarchical multilabel classification: A case study in functional geonomics, 18th Belgium-Netherlands Conference on Artificial Intelligence, BNAIC 2006, Namur, Belgium, October 5-6, 2006
  6. H. Blockeel, L. Schietgat, J. Struyf, S. Dzeroski, and A. Clare, Decision trees for hierarchical multilabel classification: a case study in functional genomics, Annual Machine Learning Conference of Belgium and The Netherlands, Benelearn 2006, Gent, Belgium, May 11-12, 2006
  7. J. Ramon, and J. Struyf, Frequent pattern mining under generalized subsumption, Dutch Belgian Database Day 2004, DBDBD 2004, Antwerpen, Belgium, December 3, 2004
  8. J. Ramon, and J. Struyf, On efficient mining of compactly represented sets of frequent patterns in relational languages, Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004,
  9. J. Struyf, J. Ramon, M. Bruynooghe, S. Verbaeten, and H. Blockeel, Compact representation of knowledge bases in inductive logic programming, 4th "Freiburg, Leuven and Friends" Workshop on Machine Learning, FLF-03, Leuven/Dourbes, Belgium, March 19-21, 2003,
  10. J. Struyf, Practical data mining applied to Spa data, Third Freiburg-Leuven Workshop on Machine Learning, Hinterzarten, Germany, February 27 - March 1, 2002
  11. J. Struyf, J. Ramon, and H. Blockeel, Compact representation of knowledge bases in ILP, Belgian-Dutch Conference on Artificial Intelligence, BNAIC'02, Leuven, Belgium, October 21-22, 2002
  12. J. Struyf, J. Ramon, and H. Blockeel, Compact representation of knowledge bases in ILP, The Twelfth International Conference on Inductive Logic Programming, ILP 2002, Sydney, Australia, July 9-11, 2002,
  13. H. Blockeel, and J. Struyf, Efficient algorithms for decision tree cross-validation, 13th Belgium-Netherlands Conference on Artificial Intelligence, BNAIC-2001, Amsterdam, The Netherlands, October 25-26, 2001, BNVKI Association
  14. H. Blockeel, and J. Struyf, Efficient multi-relational data mining, ECML/PKDD Workshop on Multi-Relational Data Mining, MRDM-2001, Freiburg, Germany, September 6, 2001
  15. H. Blockeel, and J. Struyf, Efficient algorithms for decision tree cross-validation, 2nd Leuven-Freiburg Workshop on Machine Learning, LF-01, Oostkamp, Belgium, March 14-16, 2001

Contributions at other conferences, published in proceedings

  1. J. Struyf, C. Vens, T. Croonenborghs, S. Dzeroski, and H. Blockeel, Napovedovanje funkcij genov z induktivnim logicnim programiranjem in drevesi za napovedno razvrscanje, Prvo Srecanje Slovenskih Bioinformatikov (BIOINFO2005) (Anderluh, G. and Zupan, B. and Stare, J., eds.), pp. 27-30, 2005

Contributions at other conferences, not published or only as abstract

  1. J. Struyf, Fast relational data mining - Query optimization for improving the efficiency of relational data mining systems, Industry-Ready Innovative Research: 1st Flanders Engineering PhD Symposium, Brussels, Belgium, December 11, 2003,
  2. J. Struyf, Scalable and efficient relational data mining, Faculty of Engineering, PhD Symposium, Leuven, Belgium, December 11, 2002, KUL, Faculty of Engineering

Technical reports

  1. J. Struyf, J. Ramon, M. Bruynooghe, S. Verbaeten, and H. Blockeel, Compact representation of knowledge bases in inductive logic programming, K.U.Leuven, Department of Computer Science, Report CW 377, May, 2004
  2. R. Tronçon, H. Vandecasteele, J. Struyf, B. Demoen, and G. Janssens, An execution mechanism for combining query packs and once-transformations, Department of Computer Science, K.U.Leuven, Report CW 362, Leuven, Belgium, October, 2003
  3. H. Blockeel, and J. Struyf, Efficient algorithms for decision tree cross-validation, Department of Computer Science, K.U.Leuven, Report CW 305, Leuven, Belgium, February, 2001

Edited books

  1. S. Dzeroski, and J. Struyf, Knowledge Discovery in Inductive Databases, 5th International Workshop, KDID 2006, Revised Selected and Invited Papers, vol. 4747, Lecture Notes in Computer Science, Springer, ISBN 978-3-540-75548-7, 2007

Parts of books

  1. P. Flach, H. Blockeel, T. Gartner, M. Grobelnik, B. Kavsek, M. Kejkula, D. Krzywania, N. Lavrac, P. Ljubic, D. Mladenic, S. Moyle, S. Raeymaekers, J. Rauch, S. Rawles, R. Ribeiro, G. Sclep, J. Struyf, L. Todorovski, L. Torgo, D. Wettschereck, and S. Wu, On the road to knowledge: Mining 21 Years of UK traffic accident reports, Data Mining and Decision Support: Integration and Collaboration, (Mladenic, D. and Lavrac, N. and Bohanec, M. and Moyle, S., eds.), vol. 745, The Kluwer International Series in Engineering and Computer Science, Kluwer, 2003, pp.143-156
  2. P. Flach, H. Blockeel, C. Ferri, J. Andez-Orallo, and J. Struyf, Decision support for data mining: An introduction to ROC analysis and its applications, Data Mining and Decision Support: Integration and Collaboration, (Mladenic, D. and Lavrac, N. and Bohanec, M. and Moyle, S., eds.), vol. 745, The Kluwer International Series in Engineering and Computer Science, Kluwer, 2003, pp.81-90

Thesis

  1. J. Struyf, Techniques for improving the efficiency of inductive logic programming in the context of data mining, Ph.D. Thesis, Department of Computer Science, K.U.Leuven, Leuven, Belgium, December, 2004, xx+201p+xxxv+NL16
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