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Computing Iceberg Concept Lattices with TITANIC

, , , , and . 406. University of Karlsruhe, Institute AIFB, 76128 Karlsruhe, Germany, (January 2001)

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Mining bases for association rules using closed sets, , , , and . Proceedings of the ICDE International Conference on Data Engineering, (2000)Closed Set Based Discovery of Small Covers for Association Rules., , , and . Proc. 15èmes Journées Bases de Données Avancées, BDA, page 361-381. Actes, (1999)Generating a condensed representation for association rules, and . JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, KLUWER ACADEMIC PUBLISHER, 24 (1): 29--60 (2005)Multi-objective Clustering Ensemble for Varying Number of Clusters., , and . SITIS, page 387-395. IEEE, (2018)Computing Iceberg Concept Lattices with Titanic, , , , and . Data & Knowledge Engineering, 42 (2): 189--222 (August 2002)Pascal : un algorithme d'extraction des motifs frequents, , , , and . Technique et Science Informatiques, (2000)Computing Iceberg Concept Lattices with TITANIC, , , , and . 406. University of Karlsruhe, Institute AIFB, 76128 Karlsruhe, Germany, (January 2001)Levelwise Search of Frequent Patterns, , , , and . Actes des 16 Journ Bases de Donn Avanc, Blois, France, 24-27 Octobre 2000, page 307-322. (2000)Ensemble Clustering based Semi-supervised Learning for Revenue Accounting Workflow Management., , and . DATA, page 283-293. SciTePress, (2020)Semi-supervised Consensus Clustering Based on Frequent Closed Itemsets., , , , and . CIKM, page 3341-3344. ACM, (2020)