Bart Goethals

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Toon CaldersUniversity of AntwerpVerified email at uantwerpen.be
Boris ČuleTilburg UniversityVerified email at tilburguniversity.edu
Mohammed J. ZakiProfessor & Head, Computer Science Department, RPIVerified email at cs.rpi.edu
Kris LaukensProfessor Biodata Mining & Bioinformatics, University of AntwerpVerified email at uantwerpen.be
Walter DaelemansProfessor of Computational Linguistics, University of AntwerpVerified email at uantwerpen.be
Sandy MoensUniversity of AntwerpVerified email at ua.ac.be
Pieter MeysmanAssociate professor, University of AntwerpVerified email at uantwerpen.be
Olivier JeunenPrincipal Research Scientist, AampeVerified email at aampe.com
Jan Van den BusscheProfessor, Hasselt UniversityVerified email at uhasselt.be
Geoff WebbProfessor, Department of Data Science and Artificial Intelligence, Monash UniversityVerified email at monash.edu
Len FeremansUniversiteit AntwerpenVerified email at uantwerpen.be
Taneli MielikäinenYahoo!Verified email at yahoo-inc.com
Katharina MorikProfessor of Computer Science, TU Dortmund UniversityVerified email at tu-dortmund.de
Koen Verstrepenpostdoctoral researcher, University of AntwerpVerified email at uantwerp.be
Wout BittremieuxUniversity of AntwerpVerified email at uantwerpen.be
M. Emin AkşehirliBooking.comVerified email at booking.com
Jeroen De Knijfdata scientist, Randstad GroupVerified email at randstadgroep.nl
François PetitjeanAustralian GovernmentVerified email at pm.me
Floris GeertsUniversity of AntwerpVerified email at uantwerp.be
Jilles VreekenCISPA Helmholtz Center for Information SecurityVerified email at cispa.de

Bart Goethals

Professor of Computer Science, University of Antwerp

Verified email at uantwerpen.be - Homepage

Data Mining Recommender Systems Big Data Analytics Data Science


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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	571	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	465	2010
Mining all non-derivable frequent itemsets T Calders, B Goethals Principles of Data Mining and Knowledge Discovery, 74-86, 2002	424	2002
Survey on frequent pattern mining B Goethals Univ. of Helsinki 19, 840-852, 2003	402	2003
Tiling databases F Geerts, B Goethals, T Mielikäinen Discovery Science: 7th International Conference, DS 2004, Padova, Italy …, 2004	325	2004
Frequent itemset mining for big data S Moens, E Aksehirli, B Goethals 2013 IEEE international conference on big data, 111-118, 2013	314	2013
Machine Learning and Knowledge Discovery in Databases: European Conference, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II W Daelemans, K Morik Springer, 2008	301	2008
Advances in frequent itemset mining implementations: Report on FIMI'03. B Goethals, MJ Zaki SIGKDD Explorations 6 (1), 109-117, 2004	232	2004
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	224	2019
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	215*	2018
Non-derivable itemset mining T Calders, B Goethals Data Mining and Knowledge Discovery 14, 171-206, 2007	197	2007
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	184	2013
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	181	2015
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
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	158	2011
Mining frequent itemsets in a stream T Calders, N Dexters, JJM Gillis, B Goethals Information Systems 39, 233-255, 2014	155	2014
Frequent itemset mining dataset repository B Goethals Frequent Itemset Mining Implementations (FIMI'03), 2003, 2003	138*	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	134	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	114	2005

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