| Mining closed strict episodes N Tatti, B Cule Data Mining and Knowledge Discovery 25, 34-66, 2012 | 90 | 2012 |
| Pattern based sequence classification C Zhou, B Cule, B Goethals IEEE Transactions on knowledge and Data Engineering 28 (5), 1285-1298, 2015 | 89 | 2015 |
| Selecting relevant features from the electronic health record for clinical code prediction E Scheurwegs, B Cule, K Luyckx, L Luyten, W Daelemans Journal of biomedical informatics 74, 92-103, 2017 | 62 | 2017 |
| Mining closed episodes with simultaneous events N Tatti, B Cule Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 62 | 2011 |
| Pattern-based anomaly detection in mixed-type time series L Feremans, V Vercruyssen, B Cule, W Meert, B Goethals Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 60 | 2020 |
| Grasping frequent subgraph mining for bioinformatics applications A Mrzic, P Meysman, W Bittremieux, P Moris, B Cule, B Goethals, ... BioData mining 11, 1-24, 2018 | 55 | 2018 |
| Collaborative filtering for binary, positiveonly data K Verstrepen, K Bhaduriy, B Cule, B Goethals ACM Sigkdd Explorations Newsletter 19 (1), 1-21, 2017 | 55 | 2017 |
| Mining association rules in graphs based on frequent cohesive itemsets T Hendrickx, B Cule, P Meysman, S Naulaerts, K Laukens, B Goethals Advances in Knowledge Discovery and Data Mining: 19th Pacific-Asia …, 2015 | 49 | 2015 |
| Mining train delays B Cule, B Goethals, S Tassenoy, S Verboven International Symposium on Intelligent Data Analysis, 113-124, 2011 | 47 | 2011 |
| A new constraint for mining sets in sequences B Cule, B Goethals, C Robardet Proceedings of the 2009 SIAM International Conference on Data Mining, 317-328, 2009 | 34 | 2009 |
| A pattern based predictor for event streams C Zhou, B Cule, B Goethals Expert Systems with Applications 42 (23), 9294-9306, 2015 | 30 | 2015 |
| Marbles: Mining association rules buried in long event sequences B Cule, N Tatti, B Goethals Statistical Analysis and Data Mining: The ASA Data Science Journal 7 (2), 93-110, 2014 | 22 | 2014 |
| PETSC: pattern-based embedding for time series classification L Feremans, B Cule, B Goethals Data Mining and Knowledge Discovery 36 (3), 1015-1061, 2022 | 21 | 2022 |
| Mining the entire Protein DataBank for frequent spatially cohesive amino acid patterns P Meysman, C Zhou, B Cule, B Goethals, K Laukens BioData mining 8, 1-15, 2015 | 20 | 2015 |
| Itemset based sequence classification C Zhou, B Cule, B Goethals Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013 | 18 | 2013 |
| Mining association rules in long sequences B Cule, B Goethals Advances in Knowledge Discovery and Data Mining: 14th Pacific-Asia …, 2010 | 16 | 2010 |
| Combining instance and feature neighbours for extreme multi-label classification L Feremans, B Cule, C Vens, B Goethals International Journal of Data Science and Analytics 10, 215-231, 2020 | 15 | 2020 |
| Mining Top-k Quantile-based Cohesive Sequential Patterns L Feremans, B Cule, B Goethals Proceedings of the 2018 SIAM international conference on data mining, 90-98, 2018 | 14 | 2018 |
| Efficient discovery of sets of co-occurring items in event sequences B Cule, L Feremans, B Goethals Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016 | 9 | 2016 |
| Pattern mining for learning typical turbine response during dynamic wind turbine events L Feremans, B Cule, C Devriendt, B Goethals, J Helsen International Design Engineering Technical Conferences and Computers and …, 2017 | 8 | 2017 |
Bart GoethalsProfessor of Computer Science, University of AntwerpVerified email at uantwerpen.be
