Reduction and Introducer Concepts in d-Dimensional Contexts

Abstract : Concept lattices are well-known conceptual structures that organise interesting patterns -the concepts- extracted from data. In some applications, the size of the lattice can be a problem, as it is often too large to be efficiently computed and too complex to be browsed. In others, redundant information produces noise that makes understanding the data difficult. In classical FCA, those two problems can be attenuated by, respectively, computing a substructure of the lattice -such as the AOC-poset- and reducing the context. These solutions have not been studied in d-dimensional contexts for d > 3. In this paper, we generalise the notions of AOC-poset and reduction to $d$-lattices, the structures that are obtained from multidimensional data in the same way that concept lattices are obtained from binary relations.
Complete list of metadatas

Cited literature [12 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01706404
Contributor : Giacomo Kahn <>
Submitted on : Friday, February 1, 2019 - 2:53:09 PM
Last modification on : Tuesday, July 9, 2019 - 5:33:15 PM
Long-term archiving on : Thursday, May 2, 2019 - 9:43:22 PM

File

Reduction_and_Introducers_in_d...
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01706404, version 2
  • ARXIV : 1802.04030

Citation

Alexandre Bazin, Giacomo Kahn. Reduction and Introducer Concepts in d-Dimensional Contexts. International Conference on Formal Concept Analysis, Jun 2019, Francfort, Germany. ⟨hal-01706404v2⟩

Share

Metrics

Record views

28

Files downloads

75