| On private scalar product computation for privacy-preserving data mining B Goethals, S Laur, H Lipmaa, T Mielikäinen Information Security and Cryptology–ICISC 2004, 104-120, 2005 | 567 | 2005 |
| Predicting the severity of a reported bug A Lamkanfi, S Demeyer, E Giger, B Goethals 2010 7th IEEE working conference on mining software repositories (MSR 2010 …, 2010 | 457 | 2010 |
| Mining all non-derivable frequent itemsets T Calders, B Goethals Principles of Data Mining and Knowledge Discovery, 74-86, 2002 | 418 | 2002 |
| Survey on frequent pattern mining B Goethals Univ. of Helsinki 19, 840-852, 2003 | 395 | 2003 |
| Tiling databases F Geerts, B Goethals, T Mielikäinen Discovery Science: 7th International Conference, DS 2004, Padova, Italy …, 2004 | 319 | 2004 |
| Frequent itemset mining for big data S Moens, E Aksehirli, B Goethals 2013 IEEE international conference on big data, 111-118, 2013 | 307 | 2013 |
| Advances in frequent itemset mining implementations: Report on FIMI'03. B Goethals, MJ Zaki SIGKDD Explorations 6 (1), 109-117, 2004 | 230 | 2004 |
| Analyzing concept drift and shift from sample data GI Webb, LK Lee, B Goethals, F Petitjean Data Mining and Knowledge Discovery 32, 1179-1199, 2018 | 194* | 2018 |
| Non-derivable itemset mining T Calders, B Goethals Data Mining and Knowledge Discovery 14, 171-206, 2007 | 188 | 2007 |
| Proximity forest: an effective and scalable distance-based classifier for time series B Lucas, A Shifaz, C Pelletier, L O’Neill, N Zaidi, B Goethals, F Petitjean, ... Data Mining and Knowledge Discovery 33 (3), 607-635, 2019 | 185 | 2019 |
| Clasp: An efficient algorithm for mining frequent closed sequences A Gomariz, M Campos, R Marin, B Goethals Advances in Knowledge Discovery and Data Mining: 17th Pacific-Asia …, 2013 | 177 | 2013 |
| FIMI’03: Workshop on frequent itemset mining implementations B Goethals, MJ Zaki Third IEEE International Conference on Data Mining Workshop on Frequent …, 2003 | 171 | 2003 |
| A primer to frequent itemset mining for bioinformatics S Naulaerts, P Meysman, W Bittremieux, TN Vu, W Vanden Berghe, ... Briefings in bioinformatics 16 (2), 216-231, 2015 | 170 | 2015 |
| Mining frequent itemsets in a stream T Calders, N Dexters, JJM Gillis, B Goethals Information Systems 39, 233-255, 2014 | 152 | 2014 |
| BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation AML Liekens, J De Knijf, W Daelemans, B Goethals, P De Rijk, ... Genome biology 12, 1-12, 2011 | 148 | 2011 |
| Frequent itemset mining dataset repository B Goethals Frequent Itemset Mining Implementations (FIMI'03), 2003, 2003 | 132* | 2003 |
| Automatic vandalism detection in Wikipedia: Towards a machine learning approach K Smets, B Goethals, B Verdonk AAAI workshop on Wikipedia and artificial intelligence: An Evolving Synergy …, 2008 | 131 | 2008 |
| A data mining framework for optimal product selection in retail supermarket data: the generalized PROFSET model T Brijs, B Goethals, G Swinnen, K Vanhoof, G Wets Proceedings of the sixth ACM SIGKDD international conference on knowledge …, 2000 | 130 | 2000 |
| Frequent set mining B Goethals Data mining and knowledge discovery handbook, 377-397, 2005 | 113 | 2005 |
| Unifying Nearest Neighbors Collaborative Filtering K Verstrepen, B Goethals Proceedings of the 8th ACM Conference on Recommender systems, 177-184, 2014 | 106 | 2014 |
Toon CaldersUniversity of Antwerp在 uantwerpen.be 的电子邮件经过验证
