Bart Goethals

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2008
38EEHendrik Blockeel, Toon Calders, Élisa Fromont, Bart Goethals, Adriana Prado: Mining Views: Database Views for Data Mining. ICDE 2008: 1608-1611
37EEBart Goethals, Wim Le Page, Heikki Mannila: Mining Association Rules of Simple Conjunctive Queries. SDM 2008: 96-107
2007
36 Bart Goethals: Finding interesting queries in relational databases. EGC 2007: 5
35EEToon Calders, Nele Dexters, Bart Goethals: Mining Frequent Itemsets in a Stream. ICDM 2007: 83-92
34EEToon Calders, Bart Goethals, Michael Mampaey: Mining itemsets in the presence of missing values. SAC 2007: 404-408
33EEToon Calders, Bart Goethals: Non-derivable itemset mining. Data Min. Knowl. Discov. 14(1): 171-206 (2007)
2006
32EEToon Calders, Bart Goethals, Szymon Jaroszewicz: Mining rank-correlated sets of numerical attributes. KDD 2006: 96-105
31EEToon Calders, Bart Goethals, Adriana Prado: Integrating Pattern Mining in Relational Databases. PKDD 2006: 454-461
2005
30 Bart Goethals, Arno Siebes: KDID 2004, Knowledge Discovery in Inductive Databases, Proceedings of the Third International Workshop on Knowledge Discovery inInductive Databases, Pisa, Italy, September 20, 2004, Revised Selected and Invited Papers Springer 2005
29 Bart Goethals, Eveline Hoekx, Jan Van den Bussche: Mining Tree Queries in a Graph. BNAIC 2005: 345-346
28EEBart Goethals, Eveline Hoekx, Jan Van den Bussche: Mining tree queries in a graph. KDD 2005: 61-69
27EEToon Calders, Bart Goethals: Quick Inclusion-Exclusion. KDID 2005: 86-103
26 Toon Calders, Bart Goethals: Depth-First Non-Derivable Itemset Mining. SDM 2005
25 Bart Goethals, Juho Muhonen, Hannu Toivonen: Mining Non-Derivable Association Rules. SDM 2005
24 Bart Goethals: Frequent Set Mining. The Data Mining and Knowledge Discovery Handbook 2005: 377-397
23EEFloris Geerts, Bart Goethals, Jan Van den Bussche: Tight upper bounds on the number of candidate patterns. ACM Trans. Database Syst. 30(2): 333-363 (2005)
22EEBart Goethals, Siegfried Nijssen, Mohammed Javeed Zaki: Open source data mining: workshop report. SIGKDD Explorations 7(2): 143-144 (2005)
2004
21 Roberto J. Bayardo Jr., Bart Goethals, Mohammed Javeed Zaki: FIMI '04, Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations, Brighton, UK, November 1, 2004 CEUR-WS.org 2004
20EEFloris Geerts, Bart Goethals, Taneli Mielikäinen: Tiling Databases. Discovery Science 2004: 278-289
19EEBart Goethals, Sven Laur, Helger Lipmaa, Taneli Mielikäinen: On Private Scalar Product Computation for Privacy-Preserving Data Mining. ICISC 2004: 104-120
18EEFrancesco Bonchi, Bart Goethals: FP-Bonsai: The Art of Growing and Pruning Small FP-Trees. PAKDD 2004: 155-160
17EEBart Goethals: Memory issues in frequent itemset mining. SAC 2004: 530-534
16EEBart Goethals, Mohammed Javeed Zaki: Advances in frequent itemset mining implementations: report on FIMI'03. SIGKDD Explorations 6(1): 109-117 (2004)
2003
15 Bart Goethals, Mohammed Javeed Zaki: FIMI '03, Frequent Itemset Mining Implementations, Proceedings of the ICDM 2003 Workshop on Frequent Itemset Mining Implementations, 19 December 2003, Melbourne, Florida, USA CEUR-WS.org 2003
14EEBart Goethals, Mohammed Javeed Zaki: Advances in Frequent Itemset Mining Implementations: Introduction to FIMI03. FIMI 2003
13 Floris Geerts, Bart Goethals, Taneli Mielikäinen: What You Store is What You Get. KDID 2003: 60-69
12EEToon Calders, Bart Goethals: Minimal k-Free Representations of Frequent Sets. PKDD 2003: 71-82
2002
11EEToon Calders, Bart Goethals: Mining All Non-derivable Frequent Itemsets. PKDD 2002: 74-85
10EEBart Goethals, Jan Van den Bussche: Relational Association Rules: Getting WARMeR. Pattern Detection and Discovery 2002: 125-139
9EEToon Calders, Bart Goethals: Mining All Non-Derivable Frequent Itemsets CoRR cs.DB/0206004: (2002)
8EEBart Goethals, Jan Van den Bussche: Relational Association Rules: getting WARMeR CoRR cs.DB/0206023: (2002)
2001
7 Floris Geerts, Bart Goethals, Jan Van den Bussche: A Tight Upper Bound on the Number of Candidate Patterns. ICDM 2001: 155-162
6EEFloris Geerts, Bart Goethals, Jan Van den Bussche: A Tight Upper Bound on the Number of Candidate Patterns CoRR cs.DB/0112007: (2001)
5EEBart Goethals, Jan Van den Bussche: Interactive Constrained Association Rule Mining CoRR cs.DB/0112011: (2001)
4EETom Brijs, Bart Goethals, Gilbert Swinnen, Koen Vanhoof, Geert Wets: A Data Mining Framework for Optimal Product Selection in Retail Supermarket Data: The Generalized PROFSET Model CoRR cs.DB/0112013: (2001)
2000
3EEBart Goethals, Jan Van den Bussche: On Supporting Interactive Association Rule Mining. DaWaK 2000: 307-316
2EETom Brijs, Bart Goethals, Gilbert Swinnen, Koen Vanhoof, Geert Wets: A data mining framework for optimal product selection in retail supermarket data: the generalized PROFSET model. KDD 2000: 300-304
1999
1EEBart Goethals, Jan Van den Bussche: A priori versus a posteriori filtering of association rules. 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery 1999

Coauthor Index

1Roberto J. Bayardo (Roberto J. Bayardo Jr.) [21]
2Hendrik Blockeel [38]
3Francesco Bonchi [18]
4Tom Brijs [2] [4]
5Jan Van den Bussche [1] [3] [5] [6] [7] [8] [10] [23] [28] [29]
6Toon Calders [9] [11] [12] [26] [27] [31] [32] [33] [34] [35] [38]
7Nele Dexters [35]
8Élisa Fromont [38]
9Floris Geerts [6] [7] [13] [20] [23]
10Eveline Hoekx [28] [29]
11Szymon Jaroszewicz [32]
12Sven Laur [19]
13Helger Lipmaa [19]
14Michael Mampaey [34]
15Heikki Mannila [37]
16Taneli Mielikäinen [13] [19] [20]
17Juho Muhonen [25]
18Siegfried Nijssen [22]
19Wim Le Page [37]
20Adriana Prado [31] [38]
21Arno Siebes [30]
22Gilbert Swinnen [2] [4]
23Hannu Toivonen [25]
24Koen Vanhoof [2] [4]
25Geert Wets [2] [4]
26Mohammed Javeed Zaki (Mohammed J. Zaki) [14] [15] [16] [21] [22]

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Copyright © Wed Jul 23 13:04:14 2008 by Michael Ley (ley@uni-trier.de)