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Towards Concise Representation for Taxonomies of Epistemic Communities

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Concept Lattices and Their Applications (CLA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4923))

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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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Author information

Authors and Affiliations

  1. CIRESS/LEREPS, University of Toulouse, France

    Camille Roth

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

    Sergei Obiedkov

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

    Derrick Kourie

Authors
  1. Camille Roth
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  2. Sergei Obiedkov
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  3. Derrick Kourie
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Editor information

Sadok Ben Yahia Engelbert Mephu Nguifo Radim Belohlavek

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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

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78920-8

  • Online ISBN: 978-3-540-78921-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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