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
Sandy MoensUniversity of AntwerpVerified email at ua.ac.be
Jan Van den BusscheProfessor, Hasselt UniversityVerified email at uhasselt.be
Pieter MeysmanPost-doc researcher, University of AntwerpVerified email at uantwerpen.be
Geoff WebbProfessor of Information Technology Research, Monash UniversityVerified email at monash.edu
Taneli MielikäinenYahoo!Verified email at yahoo-inc.com
Walter DaelemansProfessor of Computational Linguistics, University of AntwerpVerified email at uantwerpen.be
M. Emin AkşehirliUniversity of AntwerpVerified email at uantwerpen.be
Floris GeertsUniversity of AntwerpVerified email at uantwerp.be
Len FeremansUniversiteit AntwerpenVerified email at uantwerpen.be
Jeroen De Knijfdata scientist, Randstad GroupVerified email at randstadgroep.nl
Koen Verstrepenpostdoctoral researcher, University of AntwerpVerified email at uantwerp.be
Olivier JeunenPostdoctoral Scientist, AmazonVerified email at amazon.com
Jilles VreekenCISPA Helmholtz Center for Information SecurityVerified email at cispa.de
Wout BittremieuxUniversity of California San DiegoVerified email at ucsd.edu
François PetitjeanAustralian GovernmentVerified email at monash.edu
Trung Nghia VuKarolinska InstitutetVerified email at ki.se

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	540	2005
Mining all non-derivable frequent itemsets T Calders, B Goethals Principles of Data Mining and Knowledge Discovery, 74-86, 2002	408	2002
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	398	2010
Survey on frequent pattern mining B Goethals Univ. of Helsinki 19, 840-852, 2003	385	2003
Tiling databases F Geerts, B Goethals, T Mielikäinen International conference on discovery science, 278-289, 2004	309	2004
Frequent itemset mining for big data S Moens, E Aksehirli, B Goethals 2013 IEEE international conference on big data, 111-118, 2013	286	2013
Advances in frequent itemset mining implementations: Report on FIMI'03. B Goethals, MJ Zaki SIGKDD Explorations 6 (1), 109-117, 2004	224	2004
Non-derivable itemset mining T Calders, B Goethals Data Mining and Knowledge Discovery 14 (1), 171-206, 2007	191	2007
FIMI’03: Workshop on frequent itemset mining implementations B Goethals, MJ Zaki Third IEEE International Conference on Data Mining Workshop on Frequent …, 2003	161	2003
Clasp: An efficient algorithm for mining frequent closed sequences A Gomariz, M Campos, R Marin, B Goethals Pacific-Asia Conference on Knowledge Discovery and Data Mining, 50-61, 2013	158	2013
Mining frequent itemsets in a stream T Calders, N Dexters, JJM Gillis, B Goethals Information Systems 39, 233-255, 2014	148	2014
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	145	2015
BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation AML Liekens, J De Knijf, W Daelemans, B Goethals, P De Rijk, ... Genome biology 12 (6), 1-12, 2011	135	2011
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	124	2000
Analyzing concept drift and shift from sample data GI Webb, LK Lee, B Goethals, F Petitjean Data Mining and Knowledge Discovery 32 (5), 1179-1199, 2018	122*	2018
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	121	2008
Frequent itemset mining dataset repository B Goethals Frequent Itemset Mining Implementations (FIMI'03), 2003, 2003	119*	2003
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	111	2019
Frequent set mining B Goethals Data mining and knowledge discovery handbook, 377-397, 2005	110	2005
Unifying Nearest Neighbors Collaborative Filtering K Verstrepen, B Goethals Proceedings of the 8th ACM Conference on Recommender systems, 177-184, 2014	94	2014

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