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    Stumme, G., Taouil, R., Bastide, Y., Pasquier, N. & Lakhal, L. Computing iceberg concept lattices with TITANIC 2002 Data & Knowledge Engineering
    Vol. 42(2), pp. 189-222 
    article DOI URL 
    Abstract: We 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.
      author = {Stumme, Gerd and Taouil, Rafik and Bastide, Yves and Pasquier, Nicolas and Lakhal, Lotfi},
      title = {Computing iceberg concept lattices with TITANIC},
      journal = {Data & Knowledge Engineering},
      publisher = {Elsevier Science Publishers B. V.},
      year = {2002},
      volume = {42},
      number = {2},
      pages = {189--222},
      url = {http://portal.acm.org/citation.cfm?id=606457},
      doi = {http://dx.doi.org/10.1016/S0169-023X(02)00057-5}

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