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Classifications and Aggregation of Traces

Author

Listed:
  • Jason Xinghang Dai

    (Tech-CICO - TECHnologies pour la Coopération, l’Interaction et les COnnaissances dans les collectifs - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique - CNRS - Centre National de la Recherche Scientifique)

  • Nada Matta

    (Tech-CICO - TECHnologies pour la Coopération, l’Interaction et les COnnaissances dans les collectifs - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique - CNRS - Centre National de la Recherche Scientifique)

  • Guillaume Ducellier

    (Tech-CICO - TECHnologies pour la Coopération, l’Interaction et les COnnaissances dans les collectifs - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique - CNRS - Centre National de la Recherche Scientifique)

Abstract

The main goal of knowledge management is to promote learning from the past in an organization. Conceptual graphs use logic representation in order to allow reasoning among concepts. Currently, several works in knowledge engineering develop language as a resource description framework (RDF) and OWL in order to represent ontology in a computable form and to allow for reasoning. This chapter deals with the dynamic world, especially with cooperative processes and activities. So, the concepts are perduring concepts. In the chapter, a cooperative knowledge discovery (CKD) framework is proposed in order to obtain knowledge from traces of cooperative activities. Semantic network is used to represent knowledge structures and generic cooperative knowledge ontology is defined. CKD is based on heuristic classification and knowledge discovery principles. In addition, CKD makes explicit knowledge from cooperative activity by considering the following two aspects: knowledge representation and knowledge capturing.

Suggested Citation

  • Jason Xinghang Dai & Nada Matta & Guillaume Ducellier, 2016. "Classifications and Aggregation of Traces," Post-Print hal-02878731, HAL.
    • Handle: RePEc:hal:journl:hal-02878731
    DOI: 10.1002/9781119292142.ch4
    as

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