Can triconcepts become triclusters?

Two novel approaches to triclustering of three-way binary data are proposed. Tricluster is defined as a dense subset of a ternary relation Y defined on sets of objects, attributes, and conditions, or, equivalently, as a dense submatrix of the adjacency matrix of the ternary relation Y. This definiti...

Full description

Saved in:
Bibliographic Details
Published in:International journal of general systems 2013-08, Vol.42 (6), p.572-593
Main Authors: Ignatov, Dmitry I., Kuznetsov, Sergei O., Poelmans, Jonas, Zhukov, Leonid E.
Format: Article
Language:English
Subjects:
Algorithms
Binary data
Data mining
Equivalence
folksonomy
formal concept analysis
Matrix
Spectra
spectral triclustering
three-way data
triclustering
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Two novel approaches to triclustering of three-way binary data are proposed. Tricluster is defined as a dense subset of a ternary relation Y defined on sets of objects, attributes, and conditions, or, equivalently, as a dense submatrix of the adjacency matrix of the ternary relation Y. This definition is a scalable relaxation of the notion of triconcept in Triadic Concept Analysis, whereas each triconcept of the initial data-set is contained in a certain tricluster. This approach generalizes the one previously introduced for concept-based biclustering. We also propose a hierarchical spectral triclustering algorithm for mining dense submatrices of the adjacency matrix of the initial ternary relation Y. Finally, we describe some applications of the proposed techniques, compare proposed approaches and study their performance in a series of experiments with real data-sets.
ISSN:0308-1079
1563-5104
DOI:10.1080/03081079.2013.798899