Authors:
Teeradaj Racharak
1
and
Satoshi Tojo
2
Affiliations:
1
Sirindhorn International Institute of Technology, Thammasat University and Japan Advanced Institute of Science and Technology, Thailand
;
2
Japan Advanced Institute of Science and Technology, Japan
Keyword(s):
Concept Similarity Measure, Semantic Web Ontology, Preference Profile, Description Logics.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaboration and e-Services
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Enterprise Ontologies
;
Formal Methods
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation and Reasoning
;
Knowledge-Based Systems
;
Ontologies
;
Semantic Web
;
Simulation and Modeling
;
Soft Computing
;
Symbolic Systems
Abstract:
Concept similarity refers to human judgment of a degree to which a pair of concepts is similar. Computational
techniques attempting to imitate such judgment are called concept similarity measures. In Description Logics
(DLs), we could regard them as a generalization of the classical reasoning problem of equivalence. That is,
any two concepts are equivalent if and only if their similarity degree is one. When two concepts are not
equivalent, the level of similarity varies depending not only on the objective factors (e.g. the structure of
concept descriptions) but also on the subjective factors (i.e. the agent’s preferences). The recently introduced
notion called preference profile identified a collection of preferential elements in which any developments
for concept similarity measure should consider. In this paper, we briefly review approaches of identifying
the subsumption degree between FL0 concept descriptions and exemplify how one can adopt the viewpoint
of preference profile towa
rd the development of concept similarity measure under the agent’s preferences in
FL0. Finally, we investigate several properties of the developed measure and discuss future directions.
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