• Title/Summary/Keyword: Description Logics Inference

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Ontological Modeling of E-Catalogs using Description Logic (Description Logic을 이용한 전자카타로그 온톨로지 모델링)

  • Lee Hyunja;Shim Junho
    • Journal of KIISE:Databases
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    • v.32 no.2
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    • pp.111-119
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    • 2005
  • Electronic catalog contains ich semantics associated with products, and serves as a challenging practical domain for ontology application. Ontology is concerned with the nature and relations of being. It can play a crucial role in e-commerce as a formalization of e-Catalogs. Description Logics provide a theoretical core for most of the current ontology languages. In this paper, we present an ontological model of e-Catalogs in DL. We take an Extended Entity Relationship approach for conceptual modeling method, and present the fundamental set of modeling constructs and corresponding description language representation for each construct. Additional semantic knowledge can be represented directly in DL. Our modeling language stands within SHIQ(d) which is known reasonably practical with regard to its expressiveness and complexity. We illustrate sample scenarios to show how our approach may be utilized in modeling e-Catalogs, and also implement the scenarios through a DL inference tool to see the practical feasibility.

Boosting the Reasoning-Based Approach by Applying Structural Metrics for Ontology Alignment

  • Khiat, Abderrahmane;Benaissa, Moussa
    • Journal of Information Processing Systems
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    • v.13 no.4
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    • pp.834-851
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    • 2017
  • The amount of sources of information available on the web using ontologies as support continues to increase and is often heterogeneous and distributed. Ontology alignment is the solution to ensure semantic interoperability. In this paper, we describe a new ontology alignment approach, which consists of combining structure-based and reasoning-based approaches in order to discover new semantic correspondences between entities of different ontologies. We used the biblio test of the benchmark series and anatomy series of the Ontology Alignment Evaluation Initiative (OAEI) 2012 evaluation campaign to evaluate the performance of our approach. We compared our approach successively with LogMap and YAM++ systems. We also analyzed the contribution of our method compared to structural and semantic methods. The results obtained show that our performance provides good performance. Indeed, these results are better than those of the LogMap system in terms of precision, recall, and F-measure. Our approach has also been proven to be more relevant than YAM++ for certain types of ontologies and significantly improves the structure-based and reasoningbased methods.