Result 1 to 20 of 21 total
io-port 70208388 Mili, Hafedh;
Valtchev, Petko;
Charif, Yasmine;
Szathmary, Laszlo;
Daghrir, Nidhal;
Béland, Marjolaine;
Boubaker, Anis;
Martin, Louis;
Bédard, François;
Caid-Essebsi, Sabeh;
Al., Et
E-tourism portal: A case study in ontology-driven development (English)
MCETECH, 76-99 (2011).
1
Generating rare association rules using the minimal rare itemsets family. (English)
Int. J. Softw. Inform. 4, No. 3, 219-238 (2010).
2
Finding minimal rare itemsets and rare association rules. (English)
Bi, Yaxin (ed.) et al., Knowledge science, engineering and management. 4th international conference, KSEM 2010, Belfast, Northern Ireland, UK, September 1‒3, 2010. Proceedings. Berlin: Springer (ISBN 978-3-642-15279-5/pbk). Lecture Notes in Computer Science 6291. Lecture Notes in Artificial Intelligence, 16-27 (2010).
3
Finding minimal rare itemsets and rare association rules (English)
KSEM, 16-27 (2010).
4
Efficient vertical mining of frequent closures and generators. (English)
Adams, Niall M. (ed.) et al., Advances in intelligent data analysis VIII. 8th international symposium on intelligent data analysis, IDA 2009, Lyon, France, August 31‒September 2, 2009. Proceedings. Berlin: Springer (ISBN 978-3-642-03914-0/pbk). Lecture Notes in Computer Science 5772, 393-404 (2009).
5
Yet a faster algorithm for building the Hasse diagram of a concept lattice. (English)
Ferré, Sébastien (ed.) et al., Formal concept analysis. 7th international conference, ICFCA 2009, Darmstadt, Germany, May 21‒24, 2009. Proceedings. Berlin: Springer (ISBN 978-3-642-01814-5/pbk). Lecture Notes in Computer Science 5548. Lecture Notes in Artificial Intelligence, 162-177 (2009).
6
Yet a faster algorithm for building the Hasse diagram of a concept lattice (English)
ICFCA, 162-177 (2009).
7
Efficient vertical mining of frequent closures and generators (English)
IDA, 393-404 (2009).
8
Constructing iceberg lattices from frequent closures using generators. (English)
Boulicaut, Jean-François (ed.) et al., Discovery science. 11th international conference, DS 2008, Budapest, Hungary, October 13‒16, 2008. Proceedings. Berlin: Springer (ISBN 978-3-540-88410-1/pbk). Lecture Notes in Computer Science 5255. Lecture Notes in Artificial Intelligence, 136-147 (2008).
9
First elements on knowledge discovery guided by domain knowledge (KDDK). (English)
Ben Yahia, Sadok (ed.) et al., Concept lattices and their applications. Fourth international conference, CLA 2006, Tunis, Tunisia, October 30‒November 1, 2006. Selected papers. Berlin: Springer (ISBN 978-3-540-78920-8/pbk). Lecture Notes in Computer Science 4923. Lecture Notes in Artificial Intelligence, 22-41 (2008).
10
Constructing iceberg lattices from frequent closures using generators (English)
Discovery Science, 136-147 (2008).
11
Case base mining for adaptation knowledge acquisition. (English)
Comput. Res. Repos. 2007, Article No. 0703156 (2007).
12
Case base mining for adaptation knowledge acquisition (English)
IJCAI, 750-755 (2007).
13
ZART: A multifunctional itemset mining algorithm (English)
CLA (2007).
14
Towards rare itemset mining (English)
ICTAI (1), 305-312 (2007).
15
Adaptation knowledge discovery from a case base. (English)
Comput. Res. Repos. 2006, Article No. 0610156 (2006).
16
Vers l’extraction de motifs rares (English)
EGC, 499-510 (2006).
17
Knowledge discovery from a case base (English)
ECAI, 795-796 (2006).
18
First elements on knowledge discovery guided by domain knowledge (KDDK) (English)
CLA, 22-41 (2006).
19
Fouille de données biomédicales : apports des arbres de décision et des règles d’association à l’étude du syndrome métabolique dans la cohorte STANISLAS (English)
CAP, 361-362 (2005).
20
Result 1 to 20 of 21 total
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