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Découverte de sous-groupes à partir de données séquentielles par échantillonnage et optimisation locale.

, , and . EGC, volume E-35 of RNTI, page 153-164. Éditions RNTI, (2019)

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Supporting bi-cluster interpretation in 0/1 data by means of local patterns., , and . Intell. Data Anal., 10 (5): 457-472 (2006)Clustering Formal Concepts to Discover Biologically Relevant Knowledge from Gene Expression Data., , , , , and . In Silico Biology, 7 (4-5): 467-483 (2007)Une approche multi-paradigmes our le test d'applications BDOO., , and . BDA, INRIA, (1994)Mining Graph Topological Patterns: Finding Covariations among Vertex Descriptors., , , and . IEEE Trans. Knowl. Data Eng., 25 (9): 2090-2104 (2013)Looking for monotonicity properties of a similarity constraint on sequences., and . SAC, page 546-552. ACM, (2006)Mining Frequent Sequential Patterns under a Similarity Constraint., , and . IDEAL, volume 2412 of Lecture Notes in Computer Science, page 1-6. Springer, (2002)STARLET: An Affix-Based Compiler Compiler Designed as a Logic Programming System., and . CC, volume 477 of Lecture Notes in Computer Science, page 71-85. Springer, (1990)Actionability and Formal Concepts: A Data Mining Perspective., and . ICFCA, volume 4933 of Lecture Notes in Computer Science, page 14-31. Springer, (2008)Mining a New Fault-Tolerant Pattern Type as an Alternative to Formal Concept Discovery., , and . ICCS, volume 4068 of Lecture Notes in Computer Science, page 144-157. Springer, (2006)Query Languages for Knowledge Discovery in Databases.. PKDD, volume 1704 of Lecture Notes in Computer Science, page 582-583. Springer, (1999)