Formal Concept Analysis －Introduction, Support Softwares, and Applications－

Formal Concept Analysis, Foundations and Applications

Introduction to Formal Concept Analysis and Its Applications in Information Retrieval and Related Fields

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 concepts as basic units of human thinking and analysing data in the object-attribute form. Originated in early 80s, during the last three decades, it became a popular human-centred tool for knowledge representation a...

Linguistic Applications of Formal Concept Analysis

Formal concept analysis as a methodology of data analysis and knowledge representation has potential to be applied to a variety of linguistic problems. First, linguistic applications often involve the identification and analysis of features, such as phonemes or syntactical or grammatical markers. Formal concept analysis can be used to record and analyze such features. The line diagrams of conce...

An Introduction to Semiotic-Conceptual Analysis with Formal Concept Analysis

This paper presents a formalisation of Peirce’s notion of ‘sign’ using a triadic relation with a functional dependency. The three sign components are then modelled as concepts in lattices which are connected via a semiotic mapping. We call the study of relationships relating to semiotic systems modelled in this manner a semiotic-conceptual analysis. It is argued that semiotic-conceptual analyse...

Machine Learning methods and applications using Formal Concept Analysis

Machine learning (ML) deals with algorithms that automatically improve with experience where the experience for a ML algorithm is huge repositories of data. Machine learning methods produce a program that fits data to a model from lots of examples that specify the correct output for a given input. Formal Concept Analysis (FCA) is a successful model of learning from positive and negative example...