Diana Troanca

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The simple formalization and the intuitive graphical representation are main reasons for the growing popularity of Formal Concept Analysis (FCA). FCA gives the user the possibility to explore the structure of data and understand correlations and implications in the data set. Recently, triadic FCA (3FCA) has become increasingly popular, but exploring triadic(More)
Formal Concept Analysis (FCA) is a prominent field of applied mathematics using object-attribute relationships to define formal concepts – groups of objects with common attributes – which can be ordered into conceptual hierarchies, so-called concept lattices. We consider the problem of satisfia-bility of membership constraints, i.e., to determine if a(More)
Formal Concept Analysis (FCA) is well known for its features addressing Knowledge Processing and Knowledge Representation as well as offering a reasoning support for understanding the structure of large collections of information and knowledge. This paper aims to introduce a triadic approach to the study of web usage behavior. User dynamics is captured in(More)
Formal Concept Analysis is a prominent field of applied mathematics handling collections of knowledge-formal concepts-which are derived from some basic data types, called formal contexts by using concept forming operators. One of the strengths of FCA is the elegant, intuitive and powerful graphical representation of landscapes of knowledge as concept(More)
1 Motivation and Problem Description Conceptual knowledge is closely related to a deeper understanding of existing facts and relationships, but also to the ar-gumentation and communication of why something happens in a particular way. Formal Concept Analysis (FCA) is the core of Conceptual Knowledge Processing. It emerged from applied mathematics and(More)
Even if not explicitly stated, data can be often interpreted in a triadic setting in numerous scenarios of data analysis and processing. Formal Concept Analysis, as the underlying mathematical theory of Conceptual Knowledge Processing gives the possibility to explore the structure of data and to understand its structure. Representing knowledge as conceptual(More)
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