Three-dimensional data are increasingly prevalent across biomedical and social domains.
Notable examples are gene-sample-time, individual-feature-time, or node-node-time data …

This paper is a tutorial on Formal Concept Analysis (FCA) and its applications. FCA is an
applied branch of Lattice Theory, a mathematical discipline which enables formalisation of …

This paper presents several definitions of “optimal patterns” in triadic data and results of
experimental comparison of five triclustering algorithms on real-world and synthetic …

Mining matrices to find relevant biclusters, subsets of rows exhibiting a coherent pattern over
a subset of columns, is a critical task for a wide-set of biomedical and social applications …

In granular computing, each object is represented as an information granule and an
information granule can be connected to other granules through semantic relationships …

Statistical evaluation of biclustering solutions is essential to guarantee the absence of
spurious relations and to validate the high number of scientific statements inferred from …

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 …

Seismogenic source zone models, including the delineation and the characterization, still
have a role to play in seismic hazard calculations, particularly in regions with moderate or …

Diabetes, one of the most serious and fast growing chronic health conditions, often leads to
other serious complications such as neurological, renal, ophthalmic, and heart diseases …

Triadic concept analysis (TCA) is an extension of formal concept analysis (FCA), which can
be applied to machine learning, data mining, information retrieval, and so on. This paper …