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Concept Similarity Measures the Understanding Between Two Agents

  • Jesus M. Olivares-Ceja
  • Adolfo Guzman-Arenas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3136)

Abstract

When knowledge in each agent is represented by an ontology of concepts and relations, concept communication can not be fulfilled through exchanging concepts (ontology nodes). Instead, agents try to communicate with each other through a common language, which is often ambiguous (such as a natural language), to share knowledge. This ambiguous language, and the different concepts they master, give rise to imperfect understanding among them: How well concepts in ontology OA map to which of OB? Using a method sim that finds the most similar concept in OB corresponding to another concept in OA, we present two algorithms, one to measure the similarity between both concepts; another to gauge du, the degree of understanding that agent A has about B’s ontology. The procedures use word comparison, since no agent can measure du directly. Method sim is also compared with conf, a method that finds the confusion among words in a hierarchy. Examples follow.

Keywords

Similar Concept Symphony Orchestra Topic Hierarchy Standard Ontology Word Comparison 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Jesus M. Olivares-Ceja
    • 1
  • Adolfo Guzman-Arenas
    • 1
  1. 1.Centro de Investigacion en Computacion (CIC)Instituto Politecnico NacionalMexico

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