2010•2010 International Conference on Educational and Network TechnologyRequires access

The design and analysis of semantic web-based ontology mapping model

Xueyong Li, Wang Quanrui, Wang Shunping, Jinna Lv

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Abstract

Semantic web ontology heterogeneity is a big bottleneck of ontology application, and ontology mapping is the base for integration of heterogeneous ontology. Ontology mapping model contains several aspects, and concept similarity computing is the most important part. This paper presented an improved concept similarity computing algorithm, and on the basis of the algorithm designed an ontology mapping model. The basic idea of the algorithm is based on combining semantic-based similarity algorithm in collaborative filtering technology with concept instance algorithm in ontology mapping. In the end of this paper finished the whole mapping ontology model . After the detail discussion and analysis the experimental data of the models proved the validity of the algorithm.

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What this paper is about

Semantic web ontology heterogeneity is a big bottleneck of ontology application, and ontology mapping is the base for integration of heterogeneous ontology. Ontology mapping model contains several aspects, and concept similarity computing is the most important part. This paper presented an improved concept similarity computing algorithm, and on the basis of the algorithm designed an ontology mapping model. The basic idea of the algorithm is based on combining semantic-based similarity algorithm in collaborative filtering technology with concept instance algorithm in ontology mapping. In the end of this paper finished the whole mapping ontology model . After the detail discussion and analysis the experimental data of the models proved the validity of the algorithm.

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Available abstract

Semantic web ontology heterogeneity is a big bottleneck of ontology application, and ontology mapping is the base for integration of heterogeneous ontology. Ontology mapping model contains several aspects, and concept similarity computing is the most important part. This paper presented an improved concept similarity computing algorithm, and on the basis of the algorithm designed an ontology mapping model. The basic idea of the algorithm is based on combining semantic-based similarity algorithm in collaborative filtering technology with concept instance algorithm in ontology mapping. In the end of this paper finished the whole mapping ontology model . After the detail discussion and analysis the experimental data of the models proved the validity of the algorithm.

Key concepts: Ontology-based data integration, Computer science, Ontology, Upper ontology, Ontology alignment, Information retrieval, Ontology Inference Layer, OWL-S

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