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Authors: Teeradaj Racharak 1 and Satoshi Tojo 2

Affiliations: 1 Sirindhorn International Institute of Technology and Japan Advanced Institute of Science and Technology, Thailand ; 2 Japan Advanced Institute of Science and Technology, Japan

ISBN: 978-989-758-220-2

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: In Description Logics (DLs), concept similarity measure aims at identifying a degree of commonality of two given concepts and is often regarded 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). Realistic ontologies are generally complex. Methodologies for tuning a measure to conform with the agent’s preferences should be practical, i.e. it is doable in practice. In this work, we investigate and formalize the task of tuning the preference functions based on the information defined in a TBox and an ABox. We also show how the proposed approaches can be reconciled with the measure sim π, i.e. a concept similarity measure under preference profile for DL ELH . Fi nally, the paper relates the approach to others and discusses future direction. (More)

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Paper citation in several formats:
Racharak T. and Tojo S. (2017). Tuning Agent's Profile for Similarity Measure in Description Logic ELH.In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-220-2, pages 287-298

@conference{icaart17,
author={Teeradaj Racharak and Satoshi Tojo},
title={Tuning Agent's Profile for Similarity Measure in Description Logic ELH},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2017},
pages={287-298},
doi={},
isbn={978-989-758-220-2},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Tuning Agent's Profile for Similarity Measure in Description Logic ELH
SN - 978-989-758-220-2
AU - Racharak T.
AU - Tojo S.
PY - 2017
SP - 287
EP - 298
DO -

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