Modelling lexical databases with formal concept analysis.

This paper provides guidelines and examples for visualising lexical relations using Formal Concept Analysis. Relations in lexical databases often form trees, imperfect trees or poly-hierarchies which can be embedded into concept lattices. Many-to-many relations can be represented as concept lattices where the values from one domain are used as the formal objects and the values of the other domain as formal attributes. This paper further discusses algorithms for selecting meaningful subsets of lexical databases, the representation of complex relational structures in lexical databases and the use of lattices as basemaps for other lexical relations

Associative and Formal Concepts

In several fields there is a divide between formal and associative models of concepts and reasoning. For example, in AI associative models such as neural networks and evolutionary computation are distinguished from symbolic, logic-based approaches. In psychology, fuzzy or category-based approaches compete with the "classical" theory of classification. In information science, systems based on dynamic, emergent structures can be distinguished from formal, manually designed structures. This paper argues that both modes of representation, formal and associative ones, need to be considered simultaneously for knowledge representation systems. This paper investigates the relationship between formal and associative structures and provides suggestions for bridging the gap between the two modes of representation

A Classification of Associative and Formal Concepts

objects are thus a defining characteristic of full language: only full language can represent abstract objects