@article{pasquier2005generating,
  author = {Pasquier, Nicolas and Taouil, Rafik and Bastide, Yves and Stumme, Gerd and Lakhal, Lotfi},
  comment = {alpha},
  interhash = {cb0ee99fae39f2a5e0af5be9d97978f5},
  intrahash = {40f59a7fa7ce5015f9ee81709db89de0},
  journal = {Journal Intelligent Information Systems (JIIS)},
  number = 1,
  pages = {29-60},
  privnote = {alpha},
  publisher = {Kluwer Academic Publishers},
  title = {Generating a Condensed Representation for Association Rules},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf},
  volume = 24,
  year = 2005
}

@inbook{lakhal2005efficient,
  abstract = {Association rules are a popular knowledge discovery technique for
warehouse basket analysis. They indicate which items of the
warehouse are frequently bought together. The problem of association
rule mining has first been stated in 1993. Five years later, several
research groups discovered that this problem has a strong connection
to Formal Concept Analysis (FCA). In this survey, we will first
introduce some basic ideas of this connection along a specific
algorithm, \titanic, and show how FCA helps in reducing the number
of resulting rules without loss of information, before giving a
general overview over the history and state of the art of applying
FCA for association rule mining.},
  address = {Heidelberg},
  author = {Lakhal, Lotfi and Stumme, Gerd},
  booktitle = {Formal Concept Analysis: Foundations and Applications},
  editor = {Ganter, Bernhard and Stumme, Gerd and Wille, Rudolf},
  ee = {http://dx.doi.org/10.1007/11528784_10},
  interhash = {f5777a0f9dccfcf4f9968119d77297fc},
  intrahash = {2b350f817428e4c6c7259cd279815091},
  pages = {180-195},
  publisher = {Springer},
  series = {LNAI},
  title = {Efficient Mining of Association Rules Based on Formal Concept Analysis},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2005/lakhal2005efficient.pdf},
  volume = 3626,
  year = 2005
}

@article{pasquier2005generating,
  author = {Pasquier, Nicolas and Taouil, Rafik and Bastide, Yves and Stumme, Gerd and Lakhal, Lotfi},
  comment = {alpha},
  interhash = {cb0ee99fae39f2a5e0af5be9d97978f5},
  intrahash = {40f59a7fa7ce5015f9ee81709db89de0},
  journal = {Journal Intelligent Information Systems (JIIS)},
  number = 1,
  pages = {29-60},
  privnote = {alpha},
  publisher = {Kluwer Academic Publishers},
  title = {Generating a Condensed Representation for Association Rules},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf},
  volume = 24,
  year = 2005
}

@inbook{lakhal2005efficient,
  abstract = {Association rules are a popular knowledge discovery technique for
warehouse basket analysis. They indicate which items of the
warehouse are frequently bought together. The problem of association
rule mining has first been stated in 1993. Five years later, several
research groups discovered that this problem has a strong connection
to Formal Concept Analysis (FCA). In this survey, we will first
introduce some basic ideas of this connection along a specific
algorithm, \titanic, and show how FCA helps in reducing the number
of resulting rules without loss of information, before giving a
general overview over the history and state of the art of applying
FCA for association rule mining.},
  address = {Heidelberg},
  author = {Lakhal, Lotfi and Stumme, Gerd},
  booktitle = {Formal Concept Analysis: Foundations and Applications},
  editor = {Ganter, Bernhard and Stumme, Gerd and Wille, Rudolf},
  ee = {http://dx.doi.org/10.1007/11528784_10},
  interhash = {f5777a0f9dccfcf4f9968119d77297fc},
  intrahash = {2b350f817428e4c6c7259cd279815091},
  pages = {180-195},
  publisher = {Springer},
  series = {LNAI},
  title = {Efficient Mining of Association Rules Based on Formal Concept Analysis},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2005/lakhal2005efficient.pdf},
  volume = 3626,
  year = 2005
}

@article{stumme2002computing,
  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.},
  address = {Amsterdam, The Netherlands, The Netherlands},
  author = {Stumme, Gerd and Taouil, Rafik and Bastide, Yves and Pasquier, Nicolas and Lakhal, Lotfi},
  doi = {10.1016/S0169-023X(02)00057-5},
  interhash = {d500ac8a249ca8bf0fb05f382799d48f},
  intrahash = {fc31933f0eec502e305b6aecb9ef6e8a},
  issn = {0169-023X},
  journal = {Data \& Knowledge Engineering},
  number = 2,
  pages = {189--222},
  publisher = {Elsevier Science Publishers B. V.},
  title = {Computing iceberg concept lattices with TITANIC},
  url = {http://portal.acm.org/citation.cfm?id=606457},
  volume = 42,
  year = 2002
}