Bart Goethals

2008
45		Walter Daelemans, Bart Goethals, Katharina Morik: Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I Springer 2008
44		Walter Daelemans, Bart Goethals, Katharina Morik: Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II Springer 2008
43	EE	Hendrik Blockeel, Toon Calders, Élisa Fromont, Bart Goethals, Adriana Prado: Mining Views: Database Views for Data Mining. ICDE 2008: 1608-1611
42	EE	Roberto Trasarti, Francesco Bonchi, Bart Goethals: Sequence Mining Automata: A New Technique for Mining Frequent Sequences under Regular Expressions. ICDM 2008: 1061-1066
41	EE	Hendrik Blockeel, Toon Calders, Élisa Fromont, Bart Goethals, Adriana Prado, Céline Robardet: An inductive database prototype based on virtual mining views. KDD 2008: 1061-1064
40	EE	Bart Goethals, Wim Le Page, Heikki Mannila: Mining Association Rules of Simple Conjunctive Queries. SDM 2008: 96-107
39	EE	Walter Daelemans, Bart Goethals, Katharina Morik: Guest Editors' Introduction: Special issue of Selected Papers from ECML PKDD 2008. Data Min. Knowl. Discov. 17(1): 1-2 (2008)
38	EE	Toon Calders, Nele Dexters, Bart Goethals: Mining frequent items in a stream using flexible windows. Intell. Data Anal. 12(3): 293-304 (2008)
37	EE	Walter Daelemans, Bart Goethals, Katharina Morik: Guest Editors' introduction: special issue of selected papers from ECML PKDD 2008. Machine Learning 72(3): 155-156 (2008)
2007
36		Bart Goethals: Finding interesting queries in relational databases. EGC 2007: 5
35	EE	Toon Calders, Nele Dexters, Bart Goethals: Mining Frequent Itemsets in a Stream. ICDM 2007: 83-92
34	EE	Toon Calders, Bart Goethals, Michael Mampaey: Mining itemsets in the presence of missing values. SAC 2007: 404-408
33	EE	Toon Calders, Bart Goethals: Non-derivable itemset mining. Data Min. Knowl. Discov. 14(1): 171-206 (2007)
2006
32	EE	Toon Calders, Bart Goethals, Szymon Jaroszewicz: Mining rank-correlated sets of numerical attributes. KDD 2006: 96-105
31	EE	Toon 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
28	EE	Bart Goethals, Eveline Hoekx, Jan Van den Bussche: Mining tree queries in a graph. KDD 2005: 61-69
27	EE	Toon 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
23	EE	Floris 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)
22	EE	Bart 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
20	EE	Floris Geerts, Bart Goethals, Taneli Mielikäinen: Tiling Databases. Discovery Science 2004: 278-289
19	EE	Bart Goethals, Sven Laur, Helger Lipmaa, Taneli Mielikäinen: On Private Scalar Product Computation for Privacy-Preserving Data Mining. ICISC 2004: 104-120
18	EE	Francesco Bonchi, Bart Goethals: FP-Bonsai: The Art of Growing and Pruning Small FP-Trees. PAKDD 2004: 155-160
17	EE	Bart Goethals: Memory issues in frequent itemset mining. SAC 2004: 530-534
16	EE	Bart 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
14	EE	Bart 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
12	EE	Toon Calders, Bart Goethals: Minimal k-Free Representations of Frequent Sets. PKDD 2003: 71-82
2002
11	EE	Toon Calders, Bart Goethals: Mining All Non-derivable Frequent Itemsets. PKDD 2002: 74-85
10	EE	Bart Goethals, Jan Van den Bussche: Relational Association Rules: Getting WARMeR. Pattern Detection and Discovery 2002: 125-139
9	EE	Toon Calders, Bart Goethals: Mining All Non-Derivable Frequent Itemsets CoRR cs.DB/0206004: (2002)
8	EE	Bart Goethals, Jan Van den Bussche: Relational Association Rules: getting WARMeR CoRR cs.DB/0206023: (2002)
2001
7	EE	Floris Geerts, Bart Goethals, Jan Van den Bussche: A Tight Upper Bound on the Number of Candidate Patterns. ICDM 2001: 155-162
6	EE	Floris Geerts, Bart Goethals, Jan Van den Bussche: A Tight Upper Bound on the Number of Candidate Patterns CoRR cs.DB/0112007: (2001)
5	EE	Bart Goethals, Jan Van den Bussche: Interactive Constrained Association Rule Mining CoRR cs.DB/0112011: (2001)
4	EE	Tom 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
3	EE	Bart Goethals, Jan Van den Bussche: On Supporting Interactive Association Rule Mining. DaWaK 2000: 307-316
2	EE	Tom 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
1	EE	Bart 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

1	Roberto J. Bayardo (Roberto J. Bayardo Jr.)	[21]
2	Hendrik Blockeel	[41] [43]
3	Francesco Bonchi	[18] [42]
4	Tom Brijs	[2] [4]
5	Jan Van den Bussche	[1] [3] [5] [6] [7] [8] [10] [23] [28] [29]
6	Toon Calders	[9] [11] [12] [26] [27] [31] [32] [33] [34] [35] [38] [41] [43]
7	Walter Daelemans	[37] [39] [44] [45]
8	Nele Dexters	[35] [38]
9	Élisa Fromont	[41] [43]
10	Floris Geerts	[6] [7] [13] [20] [23]
11	Eveline Hoekx	[28] [29]
12	Szymon Jaroszewicz	[32]
13	Sven Laur	[19]
14	Helger Lipmaa	[19]
15	Michael Mampaey	[34]
16	Heikki Mannila	[40]
17	Taneli Mielikäinen	[13] [19] [20]
18	Katharina Morik	[37] [39] [44] [45]
19	Juho Muhonen	[25]
20	Siegfried Nijssen	[22]
21	Wim Le Page	[40]
22	Adriana Prado	[31] [41] [43]
23	Céline Robardet	[41]
24	Arno Siebes	[30]
25	Gilbert Swinnen	[2] [4]
26	Hannu Toivonen	[25]
27	Roberto Trasarti	[42]
28	Koen Vanhoof	[2] [4]
29	Geert Wets	[2] [4]
30	Mohammed Javeed Zaki (Mohammed J. Zaki)	[14] [15] [16] [21] [22]

Colors in the list of coauthors