Table of Contents

Publications

Books and Edited Volumes

  1. Bart Custers, Toon Calders, Bart Schermer, Tal Z. Zarsky (Eds.): Discrimination and Privacy in the Information Society - Data Mining and Profiling in Large Databases Studies in Applied Philosophy, Epistemology and Rational Ethics 3, Springer 2013, isbn 978-3-642-30486-6
  2. Mykola Pechenizkiy, Toon Calders, Cristina Conati, Sebastian Ventura, Cristobal Romero, and John Stamper (Eds.) Proceedings of the 4th International Conference on Educational Data Mining ISBN 978-90-386-2537-9, TU Eindhoven (2011)
  3. Toon Calders, Karl Tuyls, and Mykola Pechenizkiy (Eds.) Proceedings of the 21st Benelux conference on Artificial Intelligence (BNAIC) ISSN 1568-7805, TU Eindhoven (2009)
  4. C. Romero, Mykola Pechenizkiy, Toon Calders, J.E. Beck, and F. Van Assche (Eds.) Proceedings of the International Workshop on Applying Data Mining in e-Learning (ADML-2007) Vol. 305, CEUR-WS (2007)

Journal papers

  1. Hoang Thanh Lam, Fabian Morchen, Dmitriy Fradkin, and Toon Calders. Mining Compressing Sequential Patterns. In: Statistical Analysis and Data Mining. Wiley (Accepted; to appear, 2013)
  2. Nikolaj Tatti, Fabian Moerchen, and Toon Calders. Finding Robust Itemsets Under Subsampling. In: ACM Transactions on Database Systems (ACM TODS), ACM Press (In Press, to appear 2013)
  3. Toon Calders, Nele Dexters, Joris Gillis, and Bart Goethals. Mining frequent itemsets in a stream. In: Elsevier Information Systems (In Press, to appear 2013)
  4. Faisal Kamiran, Indre Zliobaite, and Toon Calders. Quantifying explainable discrimination and removing illegal discrimination in automated decision making. In: Knowledge and Information Systems (KAIS), Volume 35, Issue 3, pp 613-644 Springer (2013)
  5. Faisal Kamiran and Toon Calders. Data preprocessing techniques for classification without discrimination. In: Knowledge and Information Systems (KAIS), Volume 33, Issue 1, pp 1-33 Springer (2012)
  6. Hendrik Blockeel, Toon Calders, Elisa Fromont, Bart Goethals, Adriana Prado, and Celine Robardet. An Inductive Database System Based on Virtual Mining Views. In: Data Mining journal Vol. 24(1): pp. 247-287 (2012)
  7. Toon Calders and Mykola Pechenizkiy. Introduction to the special section on educational data mining. In: SIGKDD Explorations Vol. 13(2): pp. 3-6 (2011)
  8. Toon Calders, Dries van Dyck, and Jan Ramon. All normalized anti-monotonic overlap graph measures are bounded. In: Data Mining journal Vol. 23(3): pp. 503-548 (2011)
  9. Toon Calders and Sicco Verwer. Three Naive Bayes Approaches for Discrimination-Free Classification. In: Data Mining journal; special issue with selected papers from ECML/PKDD (2010)
  10. Chedy Raissi, Toon Calders, and Pascal Poncelet. Mining conjunctive sequential patterns. In: Data Min. Knowl. Discov. Vol. 17(1): pp. 77-93 (2008)
  11. Toon Calders, Nele Dexters, and Bart Goethals. Mining frequent items in a stream using flexible windows. In: Intell. Data Anal. Vol. 12(3): pp. 293-304 (2008)
  12. Toon Calders. Itemset frequency satisfiability: Complexity and axiomatization. In: Theor. Comput. Sci. Vol. 394(1-2): pp. 84-111 (2008)
  13. Toon Calders. The complexity of satisfying constraints on databases of transactions. In: Acta Inf. Vol. 44(7-8): pp. 591-624 (2007)
  14. Toon Calders and Bart Goethals. Non-derivable itemset mining. In: Data Min. Knowl. Discov. Vol. 14(1): pp. 171-206 (2007)
  15. Toon Calders, Nele Dexters, and Bart Goethals. A New Support Measure for Items in Streams. In: Le Monde des Utilisateurs de L'Analyse de Donnees (La Revue MODULAD) Vol. 36: pp. 37–41 (2007)
  16. Toon Calders, Laks V. S. Lakshmanan, Raymond T. Ng, and Jan Paredaens. Expressive power of an algebra for data mining. In: ACM Trans. Database Syst. Vol. 31(4): pp. 1169-1214 (2006)
  17. Toon Calders and Jan Paredaens. Axiomatization of frequent itemsets. In: Theor. Comput. Sci. Vol. 290(1): pp. 669-693 (2003)
  18. Toon Calders, Raymond T. Ng, and Jef Wijsen. Searching for dependencies at multiple abstraction levels. In: ACM Trans. Database Syst. Vol. 27(3): pp. 229-260 (2002)

Book Chapters

  1. Toon Calders, George Fletcher, Faisal Kamiran, and Mykola Pechenizkiy. Technologies for Dealing with Information Overload: An Engineers' Point of View. In: Information Overload: An International Challenge for Professional Engineers and Technical Communicators, IEEE Wiley (2012)
  2. Toon Calders and Bart H.M. Custers. What Is Data Mining and How Does It Work?. In: Discrimination and Privacy in the Information Society. Effects of Data Mining and Profiling Large Databases. Springer (2013)
  3. Toon Calders and Indre Zliobaite. Why Unbiased Computational Processes Can Lead to Discriminative Decision Procedures. In: Discrimination and Privacy in the Information Society. Effects of Data Mining and Profiling Large Databases. Springer (2013)
  4. Faisal Kamiran, Toon Calders, and Mykola Pechenizkiy. Techniques for Discrimination-Free Predictive Models. In: Discrimination and Privacy in the Information Society. Effects of Data Mining and Profiling Large Databases. Springer (2013)
  5. Sicco Verwer and Toon Calders. Introducing Positive Discrimination in Predictive Models. In: Discrimination and Privacy in the Information Society. Effects of Data Mining and Profiling Large Databases. Springer (2013)
  6. Hendrik Blockeel, Toon Calders, Elisa Fromont, Bart Goethals, Adriana Prado, and Celine Robardet. Inductive Querying with Virtual Mining Views. In: Inductive Databases and Constraint-Based Data Mining (2010)
  7. Hendrik Blockeel, Toon Calders, Elisa Fromont, Bart Goethals, Adriana Prado, and Celine Robardet. A Practical Comparative Study Of Data Mining Query Languages. In: Inductive Databases and Constraint-Based Data Mining. Springer (2010)
  8. Enrique Garcia, Cristobal Romero, Sebastian Ventura, Carlos de Castro, and Toon Calders. Chapter 7: Association Rule Mining in Learning Management Systems. In: Handbook of Educational Data Mining, Taylor & Francis Group (2010)
  9. Toon Calders, Christophe Rigotti, and Jean-Francois Boulicaut. A Survey on Condensed Representations for Frequent Sets. In: Constraint-Based Mining and Inductive Databases: pp. 64-80. Springer (2006)

Articles in Conference and Workshop Proceedings

  1. Toon Calders, Elisa Fromont, Baptiste Jeudy and Hoang Thanh Lam. Analysis of Videos using Tile Mining. In: RealStream workshop at ECML PKDD 2013.
  2. Hoang Thanh Lam, Wenjie Pei, Adriana Prado, Baptiste Jeudy, Élisa Fromont, and Toon Calders. Extraction des top-k plus grandes tuiles dans un flux de données. CAP (2013)
  3. Elias Egho, Chedy Raïssi, Toon Calders, Thomas Bourquard, Nicolas Jay, Amedeo Napoli. Vers une mesure de similarité pour les séquences complexes. EGC 2013: 335-340 (2013)
  4. Toon Calders. Recent Developments in Pattern Mining. Proceedings ALT: 34 (2012)
  5. Toon Calders. Recent Developments in Pattern Mining. Proceedings Discovery Science: 2 (2012)
  6. Toon Calders and Mykola Pechenizkiy. Cost-Sensitive Classification Problem. In: Workshop on Teachning Machine Learning (TML) at ICML (2012)
  7. Hoang Thanh Lam, Fabian Moerchen, Dimitry Fradkin, and Toon Calders. Mining compressing sequential patterns. In: SIAM Data Mining Conference (SDM) (2012)
  8. Indre Zliobaite, Faisal Kamiran, and Toon Calders. Handling Conditional Discrimination. In: Proceedings IEEE ICDM International Conference on Data Mining (2011)
  9. Hoang Thanh Lam, Ninh Dang Pham, and Toon Calders. Online Discovery of Top-k Similar Motifs in Time Series Data. In: SIAM Data Mining Conference (SDM) (2011)
  10. Faisal Kamiran, Toon Calders, and Mykola Pechenizkiy. Discrimination Aware Decision Tree Learning. In: Proceedings IEEE ICDM International Conference on Data Mining (2010)
  11. Toon Calders, Calin Garboni, and Bart Goethals. Approximating Frequentness Probability of Itemsets in Uncertain Data. In: Proceedings IEEE ICDM International Conference on Data Mining (2010)
  12. Faisal Kamiran and Toon Calders. Classification Without Discrimination by Preferential Sampling. In: Proceedings Benelearn conference (2010)
  13. Hoang Thanh Lam and Toon Calders. Mining Top-K Frequent Items in a Data Stream with Flexible Sliding Windows. In: Proceedings ACM SIGKDD (2010)
  14. Arno J. Knobbe, Hendrik Blockeel, Arne Koopman, Toon Calders, Bas Obladen, Carlos Bosma, Hessel Galenkamp, Eddy Koenders, and Joost N. Kok. InfraWatch: Data Management of Large Systems for Monitoring Infrastructural Performance. In: IDA: pp. 91-102 (2010)
  15. Toon Calders, Calin Garboni, and Bart Goethals. Efficient Pattern Mining of Uncertain Data with Sampling. In: PAKDD (1): pp. 480-487 (2010)
  16. Toon Calders, Faisal Kamiran, and Mykola Pechenizkiy. Building Classifiers with Independency Constraints. In: IEEE ICDM Workshop Domain Driven Data Mining (DDDM): pp. 13-18 (2009)
  17. Toon Calders, Christian W. Guenther, Mykola Pechenizkiy, and Anne Rozinat. Using minimum description length for process mining. In: SAC: pp. 1451-1455 (2009)
  18. Faisal Kamiran and Toon Calders. Classification Without Discrimination. In: IEEE International Conference on Computer, Control and Communication (IEEE-IC4), IEEE Press (2009)
  19. Faisal Kamiran and Toon Calders. Discrimination-Aware Classification (Extended Abstract). In: 21st Benelux Conference on Artificial Intelligence (BNAIC): pp. 333-334 (2009)
  20. Chedy Raissi, Toon Calders, and Pascal Poncelet. Mining Conjunctive Sequential Patterns: Extended Abstract. In: ECML/PKDD (1): pp. 19 (2008)
  21. Mykola Pechenizkiy, Toon Calders, Ekaterina Vasilyeva, and Paul De Bra. Mining the Student Assessment Data: Lessons Drawn from a Small Scale Case Study. In: EDM: pp. 187-191 (2008)
  22. Hendrik Blockeel, Toon Calders, Elisa Fromont, Bart Goethals, and Adriana Prado. Mining Views: Database Views for Data Mining. In: ICDE: pp. 1608-1611 (2008)
  23. Hendrik Blockeel, Toon Calders, Élisa Fromont, Bart Goethals, Adriana Prado, and Céline Robardet. An inductive database prototype based on virtual mining views. In: KDD: pp. 1061-1064 (2008)
  24. Toon Calders, Jan Ramon, and Dries Van Dyck. Anti-monotonic Overlap-Graph Support Measures. In: ICDM: pp. 73-82 (2008)
  25. Toon Calders, Jan Ramon, and Dries Van Dyck. Min, Max and PTIME Anti-Monotonic Overlap Graph Measures. In: 6th International Workshop on Mining and Learning with Graphs (MLG) (2008)
  26. Joseph E. Beck, Toon Calders, Mykola Pechenizkiy, and Silvia Rita Viola. Workshop on Educational Data Mining @ ICALT07 (EDM@ICALT07). In: ICALT: pp. 933-934 (2007)
  27. Toon Calders, Nele Dexters, and Bart Goethals. Mining Frequent Itemsets in a Stream. In: ICDM: pp. 83-92 (2007)
  28. Toon Calders and Szymon Jaroszewicz. Efficient AUC Optimization for Classification. In: PKDD: pp. 42-53 (2007)
  29. Toon Calders, Bart Goethals, and Michael Mampaey. Mining itemsets in the presence of missing values. In: SAC: pp. 404-408 (2007)
  30. Hendrik Blockeel, Toon Calders, Élisa Fromont, Bart Goethals, and Adriana Prado. Mining Views: Database Views for Data Mining. In: ECML/PKDD-2007 International Workshop on Constraint-Based Mining and Learning (CMILE) (2007)
  31. E. Garcia, C. Romero, S. Ventura, and Toon Calders. Drawbacks and solutions of applying association rule mining in learning management systems. In: Proc. EC-TEL07 Workshop on Applying Data Mining in e-Learning (ADML-07) (2007)
  32. Mykola Pechenizkiy and Toon Calders. A Framework for Guiding the Museum Tour Personalization. In: Proceedings UM 2007 International Workshop on Personalization Enhanced Access to Cultural Heritage (CHIP) (2007)
  33. Toon Calders, Bart Goethals, and Szymon Jaroszewicz. Mining rank-correlated sets of numerical attributes. In: KDD: pp. 96-105 (2006)
  34. Toon Calders, Bart Goethals, and Adriana Prado. Integrating Pattern Mining in Relational Databases. In: PKDD: pp. 454-461 (2006)
  35. Toon Calders, Stijn Dekeyser, Jan Hidders, and Jan Paredaens. Analyzing workflows implied by instance-dependent access rules. In: PODS: pp. 100-109 (2006)
  36. Toon Calders, Nele Dexters, and Bart Goethals. Mining Frequent Items in a Stream Using Flexible Windows. In: ECML/PKDD-2006 International Workshop on Knowledge Discovery from Data Streams (IWKDDS) (2006)
  37. Andy Zaidman, Toon Calders, Serge Demeyer, and Jan Paredaens. Applying Webmining Techniques to Execution Traces to Support the Program Comprehension Process. In: CSMR: pp. 134-142 (2005)
  38. Toon Calders and Bart Goethals. Quick Inclusion-Exclusion. In: KDID: pp. 86-103 (2005)
  39. Toon Calders and Bart Goethals. Depth-First Non-Derivable Itemset Mining. In: SDM (2005)
  40. Andy Zaidman, Toon Calders, Serge Demeyer, and Jan Paredaens. Selective Introduction of Aspects for Program Comprehension. In: WCRE Workshop on Aspect Reverse Engineering (WARE) (2004)
  41. Nele Dexters and Toon Calders. Theoretical Bounds on the Size of Condensed Representations. In: KDID: pp. 46-65 (2004)
  42. Toon Calders. Deducing Bounds on the Support of Itemsets. In: Database Support for Data Mining Applications: pp. 214-233 Springer (2004)
  43. Toon Calders. Computational Complexity of Itemset Frequency Satisfiability. In: PODS: pp. 143-154 (2004)
  44. Toon Calders and Bart Goethals. Minimal k-Free Representations of Frequent Sets. In: PKDD: pp. 71-82 (2003)
  45. Toon Calders and Bart Goethals. Mining All Non-derivable Frequent Itemsets. In: PKDD: pp. 74-85 (2002)
  46. Toon Calders. Deducing Bounds on the Frequency of Itemsets. In: EDBT Workshop DTDM Database Techniques in Data Mining (2002)
  47. Toon Calders and Jef Wijsen. On Monotone Data Mining Languages. In: DBPL: pp. 119-132 (2001)
  48. Toon Calders and Jan Paredaens. Axiomatization of Frequent Sets. In: ICDT: pp. 204-218 (2001)
  49. Toon Calders and Jan Paredaens. Mining Frequent Binary Expressions. In: DaWaK: pp. 399-408 (2000)
  50. Jef Wijsen, Raymond T. Ng, and Toon Calders. Discovering Roll-Up Dependencies. In: KDD: pp. 213-222 (1999)

Technical Reports and Theses

  1. Faisal Kamiran, Toon Calders, and Mykola Pechenizkiy. Discrimination Aware Decision Tree Learning. Eindhoven University of Technology, Dept. Math. and Computer Science(CS-Report 10-13) (2010)
  2. An De Sitter, Toon Calders, and Walter Daelemans. A Formal Framework for Evaluation of Information Extraction. University of Antwerp, Dept. Math. and Computer Science(2004-04) (2004)
  3. Toon Calders. Axiomatization and Deduction Rules for the Frequency of Itemsets. PhD thesis University of Antwerp, Dept. Math. and Computer Science (2003)
  4. Toon Calders and Jef Wijsen. On Monotone Data Mining Languages. University of Antwerp, Dept. Math. and Computer Science(2001-08) (2001)
  5. Toon Calders and Jan Paredaens. Mining Binary Expressions: Applications and Algorithms. University of Antwerp, Dept. Math. and Computer Science(2000-08) (2000)
  6. Toon Calders and Jan Paredaens. A Theoretical Framework for Reasoning about Frequent Itemsets. University of Antwerp, Dept. Math. and Computer Science(2000-06) (2000)
  7. Toon Calders. Het ontdekken van roll-up afhankelijkheden in databases. Master thesis University of Antwerp, Dept. Math. and Computer Science (1999)