Formal Concept Analysis (FCA) has typically been applied in the field of software engineering to support software maintenance and object-oriented class identification tasks. This paper presents a broader overview by describing and classifying academic papers that report the application of FCA to software engineering. The papers are classified using a framework based on the activities defined in...

Latent Semantic Indexing (LSI), a variant of classical Vector Space Model (VSM), is an Information Retrieval (IR) model that attempts to capture the latent semantic relationship between the data items. Mathematical lattices, under the framework of Formal Concept Analysis (FCA), represent conceptual hierarchies in data and retrieve the information. However, both LSI and FCA use the data represen...

The paper presents a new method of decision tree induction based on formal concept analysis (FCA). The decision tree is derived using a concept lattice, i.e. a hierarchy of clusters provided by FCA. The idea behind is to look at a concept lattice as a collection of overlapping trees. The main purpose of the paper is to explore the possibility of using FCA in the problem of decision tree inducti...

This paper views Formal Concept Analysis (FCA) from an educational perspective. Novice users of FCA who are not mathematicians might find diagrams of concept lattices counter-intuitive and challenging to read. According to educational theory, learning thresholds are concepts that are difficult to learn and easy to be misunderstood. Experts of a domain are often not aware of such learning thresh...

Association rules are a popular knowledge discovery technique for warehouse basket analysis. They indicate which items of the warehouse are frequently bought together. The problem of association rule mining has first been stated in 1993. Five years later, several research groups discovered that this problem has a strong connection to Formal Concept Analysis (FCA). In this survey, we will first ...

Formal concept analysis (FCA) is a method of exploratory data analysis. The data is in the form of a table describing relationship between objects (rows) and attributes (columns), where table entries are grades representing degrees to which objects have attributes. The main output of FCA is a hierarchical structure (so-called concept lattice) of conceptual clusters (so-called formal concepts) p...

The paper uses Formal Concept Analysis (FCA) to replicate the results of a study that employed fuzzy set Qualitative Comparative Analysis (fsQCA) to determine the configurational conditions that are necessary or sufficient to explain the participation of top banks in a multistakeholder agreement against money laundering. Using raw input data from a previous study, the same result regarding nece...

Rough set theory (RST) and formal concept analysis (FCA) are two formal settings in information management, which have found applications in learning and in data mining. Both rely on a binary relation. FCA starts with a formal context, which is a relation linking a set of objects with their properties. Besides, a rough set is a pair of lower and upper approximations of a set of objects induced ...

The timely transition from vegetative to reproductive growth is vital for reproductive success in plants. It has been suggested that messenger RNA 3'-end processing plays a role in this transition. Specifically, two autonomous factors in the Arabidopsis thaliana flowering time control pathway, FY and FCA, are required for the alternative polyadenylation of FCA pre-mRNA. In this paper we provide...