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.
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Olivares-Ceja, J.M., Guzman-Arenas, A. (2004). Concept Similarity Measures the Understanding Between Two Agents. In: Meziane, F., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2004. Lecture Notes in Computer Science, vol 3136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27779-8_16
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DOI: https://doi.org/10.1007/978-3-540-27779-8_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22564-5
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