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We present an approach to the cell formation problem, known from group technology, which is inspired by formal concept analysis. The cell formation problem consists in allocating parts (objects) to machines (attributes), based on the machine-part matrix. This can be viewed as forming groups consisting of a set of parts and a set of machines. Such groups resemble formal concepts in the input data....
This paper describes a method to identify so-called ecological traits of species based on the analysis of their biological characteristics. This biological dataset has a complex structure that can be formalized as a fuzzy many-valued context and transformed into a binary context through histogram scaling. The core of the method relied on the construction and interpretation of formal concepts and was...
Standard Support Vector Machines (SVM) text classification relies on bag-of-words kernel to express the similarity between documents. We show that a document lattice can be used to define a valid kernel function that takes into account the relations between different terms. Such a kernel is based on the notion of conceptual proximity between pairs of terms, as encoded in the document lattice. We describe...
Gene expression data are numerical and describe the level of expression of genes in different situations, thus featuring behaviour of the genes. Two methods based on FCA (Formal Concept Analysis) are considered for clustering gene expression data. The first one is based on interordinal scaling and can be realized using standard FCA algorithms. The second method is based on pattern structures and needs...
Following the advent of information technology and the rapid growth of its application in the medical field, the picture archiving and communication system (PACS) became very popular in mid- to large-scale hospitals. This study aimed to compare the concept lattice of radiology report content before and after the adoption of PACS. This study proposes a formal concept analysis process to produce different...
This paper revisits the lattice-based thesaurus models which Margaret Masterman used for machine translation in the 1950’s and 60’s. Masterman’s notions are mapped onto modern, Formal Concept Analysis (FCA) terminology and three of her thesaurus algorithms are formalised with FCA methods. The impact of the historical and social situatedness of Roget’s Thesaurus on such algorithms is considered. The...
We propose a concept lattice-based approach to multiple two dimensional pattern matching problems. It is assumed that a pattern can be described as a set of vertices (or pixels) and that a small set of vertices around each vertex corresponds to an attribute in a concept lattice. Typically, an attribute should be a succinct characterisation of domain-dependent relevant information about the neighbourhood...
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