Special Issue: Concept Lattices and Their ApplicationsNo Access

ON SUCCINCT REPRESENTATION OF KNOWLEDGE COMMUNITY TAXONOMIES WITH FORMAL CONCEPT ANALYSIS

CAMILLE ROTH

Center of Research in Social Simulation (CRESS), Department of Sociology, University of Surrey, UK

European Center for Living Technology, Venice, Italy

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SERGEI OBIEDKOV

Department of Applied Mathematics, Higher School of Economics, Moscow, Russia

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, and

DERRICK G. KOURIE

Department of Computer Science, University of Pretoria, Pretoria, South Africa

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https://doi.org/10.1142/S0129054108005735Cited by:40 (Source: Crossref)

Abstract

We present an application of formal concept analysis aimed at representing a meaningful structure of knowledge communities in the form of a lattice-based taxonomy. The taxonomy groups together agents (community members) who develop a set of notions. If no constraints are imposed on how it is built, a knowledge community taxonomy may become extremely complex and difficult to analyze. We consider two approaches to building a concise representation, respecting the underlying structural relationships while hiding superfluous information: a pruning strategy based on the notion of concept stability and a representational improvement based on nested line diagrams and "zooming". We illustrate the methods on two examples: a community of embryologists and a community of researchers in complex systems.

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