| A quickstart in frequent structure mining can make a difference S Nijssen, JN Kok Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004 | 716 | 2004 |
| Frequent subtree mining–an overview Y Chi, RR Muntz, S Nijssen, JN Kok Fundamenta Informaticae 66 (1-2), 161-198, 2005 | 339 | 2005 |
| What is frequent in a single graph? B Bringmann, S Nijssen Advances in Knowledge Discovery and Data Mining: 12th Pacific-Asia …, 2008 | 264 | 2008 |
| Itemset mining: A constraint programming perspective T Guns, S Nijssen, L De Raedt Artificial Intelligence 175 (12-13), 1951-1983, 2011 | 235 | 2011 |
| The gaston tool for frequent subgraph mining S Nijssen, JN Kok Electronic Notes in Theoretical Computer Science 127 (1), 77-87, 2005 | 223 | 2005 |
| Constraint programming for itemset mining L De Raedt, T Guns, S Nijssen Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 220 | 2008 |
| Efficient discovery of frequent unordered trees S Nijssen, JN Kok First international workshop on mining graphs, trees and sequences 2003, 2003 | 169 | 2003 |
| Faster association rules for multiple relations S Nijssen, J Kok International joint conference on artificial intelligence 17 (1), 891-896, 2001 | 136 | 2001 |
| Substructure mining using elaborate chemical representation J Kazius, S Nijssen, J Kok, T Bäck, AP IJzerman Journal of Chemical Information and Modeling 46 (2), 597-605, 2006 | 106 | 2006 |
| Learning optimal decision trees using caching branch-and-bound search G Aglin, S Nijssen, P Schaus Proceedings of the AAAI conference on artificial intelligence 34 (04), 3146-3153, 2020 | 104 | 2020 |
| Correlated itemset mining in ROC space: a constraint programming approach S Nijssen, T Guns, L De Raedt Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 102 | 2009 |
| Mining optimal decision trees from itemset lattices S Nijssen, E Fromont Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007 | 93 | 2007 |
| Constraint programming for data mining and machine learning L De Raedt, T Guns, S Nijssen Proceedings of the AAAI Conference on Artificial Intelligence 24 (1), 1671-1675, 2010 | 91 | 2010 |
| Learning optimal decision trees using constraint programming H Verhaeghe, S Nijssen, G Pesant, CG Quimper, P Schaus Constraints 25, 226-250, 2020 | 84 | 2020 |
| k-Pattern set mining under constraints T Guns, S Nijssen, L De Raedt IEEE Transactions on Knowledge and Data Engineering 25 (2), 402-418, 2011 | 84 | 2011 |
| Pattern-based classification: A unifying perspective B Bringmann, S Nijssen, A Zimmermann arXiv preprint arXiv:1111.6191, 2011 | 79 | 2011 |
| Don’t be afraid of simpler patterns B Bringmann, A Zimmermann, L De Raedt, S Nijssen European Conference on Principles of Data Mining and Knowledge Discovery, 55-66, 2006 | 79 | 2006 |
| Efficient Frequent Query Discovery in Farmer S Nijssen, JN Kok European Conference on Principles of Data Mining and Knowledge Discovery …, 2003 | 74 | 2003 |
| Constrained clustering using column generation B Babaki, T Guns, S Nijssen Integration of AI and OR Techniques in Constraint Programming: 11th …, 2014 | 73 | 2014 |
| Frequent graph mining and its application to molecular databases S Nijssen, JN Kok 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat …, 2004 | 73 | 2004 |
Luc De Raedtprofessor, KU Leuven & guestprofessor, Örebro UniversityVerified email at cs.kuleuven.be
