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Conference Papers Year : 2016

Knowledge Engineering Method Based on Consensual Knowledge and Trust Computation: The MUSCKA System

Abstract

We propose a method for building a knowledge base addressing specific issues such as covering an end-users' need and reuse non-ontological sources such as thesauri or classifications. After designing an ontology module representing the knowledge needed by end-users, we enrich and populate it automatically with knowledge extracted from existing sources. The originality of our proposition is to propose ontological object candidates from existing sources according to both their relatedness to the ontological module and to computed measures of trust. This paper describes the trust measures we propose which are obtained by analysing the consensus found in existing sources. Thus we consider that knowledge are more reliable if it has been extracted from several sources. The use of these measures has been evaluated on a real case study with experts from the agriculture domain
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Dates and versions

hal-01709185 , version 1 (14-02-2018)

Identifiers

  • HAL Id : hal-01709185 , version 1
  • OATAO : 18839

Cite

Fabien Amarger, Jean-Pierre Chanet, Ollivier Haemmerlé, Nathalie Jane Hernandez, Catherine Roussey. Knowledge Engineering Method Based on Consensual Knowledge and Trust Computation: The MUSCKA System. International Conference on Conceptual Structures (ICCS 2016), Jul 2016, Annecy, France. pp. 177-190. ⟨hal-01709185⟩
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