Formal context coverage based on isolated labels: An efficient solution for text feature extraction

Different available data as images, texts, or database may be mapped into an equivalent or approximate binary relation. A text may be considered as a binary relation relating sentences to words, while a numerical table may be represented by a binary relation after using some scaling approach. A social network may be also represented by a formal context. The objective of this paper is to present an original approach for covering a binary relation by formal concepts based on isolated single or multiple properties, i.e., those belonging to only one concept. As a matter of fact, isolated properties are efficiently used for discriminating and labeling concepts. The latter are used for browsing in a corpora, or in a document by navigating through associated labels. By using fringe relations, the presented approach compared to those of the literature has the advantage of offering a relevant feature of a context by significant labels. Carried out experiments show the benefits of the introduced approach.