JournalArticlestumme2002computingComputing iceberg concept lattices with TITANIC2002StummeGerdTaouilRafikBastideYvesPasquierNicolasLakhalLotfi189-22242 ISSN: 0169-023X DOI: 10.1016/S0169-023X(02)00057-5Elsevier Science Publishers B. V.Amsterdam, The Netherlands, The NetherlandsData \& Knowledge Engineering2Augusthttp://portal.acm.org/citation.cfm?id=606457We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suited for analyzing very large databases. They also serve as a condensed representation of frequent itemsets, as starting point for computing bases of association rules, and as a visualization method for association rules. Iceberg concept lattices are based on the theory of Formal Concept Analysis, a mathematical theory with applications in data analysis, information retrieval, and knowledge discovery. We present a new algorithm called TITANIC for computing (iceberg) concept lattices. It is based on data mining techniques with a level-wise approach. In fact, TITANIC can be used for a more general problem: Computing arbitrary closure systems when the closure operator comes along with a so-called weight function. The use of weight functions for computing closure systems has not been discussed in the literature up to now. Applications providing such a weight function include association rule mining, functional dependencies in databases, conceptual clustering, and ontology engineering. The algorithm is experimentally evaluated and compared with Ganter's Next-Closure algorithm. The evaluation shows an important gain in efficiency, especially for weakly correlated data.lattice, titanic, concept, formal, iceberg, analysis, fcaConferenceProceedingsinproceedingspasquier98pruningPruning closed itemset lattices for associations rules.1998PasquierNicolasBastideYvesTaouilRafikLakhalLotfiBouzeghoubMokraneBases de Donn�es Avanc�esBases de Donn�es Avanc�eshttp://dblp.uni-trier.de/db/conf/bda/bda98.html#PasquierBTL98rules, closed, concept, formal, association, OntologyHandbook, FCA, analysis, fca, itemset, miningconf/bda/1998JournalArticlepasquier2005generatingGenerating a Condensed Representation for Association Rules2005PasquierNicolasTaouilRafikBastideYvesStummeGerdLakhalLotfi29-6024Kluwer Academic PublishersJournal Intelligent Information Systems (JIIS)1http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdfconcept, discovery, 2005, association, OntologyHandbook, l3s, analysis, kdd, itemset, myown, rule, data, knowledge, closed, formal, rules, itegpub, condensed, fca, sets, representations, miningJournalArticlepasquier2005generatingGenerating a Condensed Representation for Association Rules2005PasquierNicolasTaouilRafikBastideYvesStummeGerdLakhalLotfi29-6024Kluwer Academic PublishersJournal Intelligent Information Systems (JIIS)1http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdfconcept, discovery, 2005, association, OntologyHandbook, l3s, analysis, kdd, itemset, myown, rule, data, knowledge, closed, formal, rules, itegpub, condensed, fca, sets, representations, miningConferenceProceedingsinproceedingspasquier98pruningPruning closed itemset lattices for associations rules.1998PasquierNicolasBastideYvesTaouilRafikLakhalLotfiBouzeghoubMokraneBases de Données AvancéesBases de Données Avancéeshttp://dblp.uni-trier.de/db/conf/bda/bda98.html#PasquierBTL98rules, closed, concept, formal, association, analysis, fca, itemset, miningconf/bda/1998JournalArticlestumme2002computingComputing iceberg concept lattices with TITANIC2002StummeGerdTaouilRafikBastideYvesPasquierNicolasLakhalLotfi189-22242 ISSN: 0169-023X DOI: 10.1016/S0169-023X(02)00057-5Elsevier Science Publishers B. V.Amsterdam, The Netherlands, The NetherlandsData & Knowledge Engineering2Augusthttp://portal.acm.org/citation.cfm?id=606457We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suited for analyzing very large databases. They also serve as a condensed representation of frequent itemsets, as starting point for computing bases of association rules, and as a visualization method for association rules. Iceberg concept lattices are based on the theory of Formal Concept Analysis, a mathematical theory with applications in data analysis, information retrieval, and knowledge discovery. We present a new algorithm called TITANIC for computing (iceberg) concept lattices. It is based on data mining techniques with a level-wise approach. In fact, TITANIC can be used for a more general problem: Computing arbitrary closure systems when the closure operator comes along with a so-called weight function. The use of weight functions for computing closure systems has not been discussed in the literature up to now. Applications providing such a weight function include association rule mining, functional dependencies in databases, conceptual clustering, and ontology engineering. The algorithm is experimentally evaluated and compared with Ganter's Next-Closure algorithm. The evaluation shows an important gain in efficiency, especially for weakly correlated data.titanic, concept, iceberg, fca, kdd, computing