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 interact and/or develop a set of notions—i.e. cognitive properties of group members. In the absence of appropriate constraints on how it is built, a knowledge community taxonomy is in danger of becoming extremely complex, and thus difficult to comprehend. We consider two approaches to building a concise representation that respects the underlying structural relationships, while hiding uninteresting and/or superfluous information. The first is a pruning strategy that is based on the notion of concept stability, and the second is a representational improvement based on nested line diagrams. We illustrate the method with a small sample of a community of embryologists.
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Roth, C., Obiedkov, S., Kourie, D. (2008). Towards Concise Representation for Taxonomies of Epistemic Communities. In: Yahia, S.B., Nguifo, E.M., Belohlavek, R. (eds) Concept Lattices and Their Applications. CLA 2006. Lecture Notes in Computer Science(), vol 4923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78921-5_17
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DOI: https://doi.org/10.1007/978-3-540-78921-5_17
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