Abstract
Analysis of polyadic data (for example n-ary relations) becomes a popular task nowadays. While several data mining techniques exist for dyadic contexts, their extensions to triadic case are not obvious. In this work, we study development of ideas of Formal Concept Analysis for processing three-dimensional data, namely OAC-triclustering (from Object, Attribute, Condition). We consider several similar methods, study relations between their outputs and organize them in an ordered structure.
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Acknowledgments
We would like to thank our colleagues, B. Ganter, S. Kuznetsov, B. Mirkin, R. Missaoui, L. Cerf, J.-F. Boulicaut, A. Napoli, M. Kaytoue and S. Ben Yahia for their piece of advice and useful prior communication. The paper was prepared within the framework of the Basic Research Program at HSE and supported within the framework of a subsidy by the Russian Academic Excellence Project “5–100”. The second co-author was partially supported by Russian Foundation for Basic Research. This work was also partially supported by the French LabEx project IMobS3.
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Egurnov, D., Ignatov, D.I., Mephu Nguifo, E. (2017). On Containment of Triclusters Collections Generated by Quantified Box Operators. In: Kryszkiewicz, M., Appice, A., Ślęzak, D., Rybinski, H., Skowron, A., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2017. Lecture Notes in Computer Science(), vol 10352. Springer, Cham. https://doi.org/10.1007/978-3-319-60438-1_56
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DOI: https://doi.org/10.1007/978-3-319-60438-1_56
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