@inproceedings{jaeschke2006trias,
  abstract = {In this paper, we present the foundations for mining frequent tri-concepts, which extend the notion of closed itemsets to three-dimensional data to allow for mining folk-sonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution as well as experimental results on a large real-world example.},
  address = {Washington, DC, USA},
  author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
  booktitle = {ICDM '06: Proceedings of the Sixth International Conference on Data Mining},
  doi = {10.1109/ICDM.2006.162},
  interhash = {b4964c3bdd2991a80873d7080ef6a73e},
  intrahash = {797d40e05a48f4343d7695dac87b5870},
  isbn = {0-7695-2701-9},
  pages = {907--911},
  publisher = {IEEE Computer Society},
  title = {TRIAS - An Algorithm for Mining Iceberg Tri-Lattices},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/jaeschke2006trias.pdf},
  year = 2006
}

@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},
  month = aug,
  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
}