CENTRALIZED CLUSTERING METHOD TO INCREASE ACCURACY IN ONTOLOGY MATCHING SYSTEMS

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BABALOU SAMIRA; KARGAR MOHAMMAD JAVAD; DAVARPANAH SEYYED HASHEM

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Journal Paper

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Journal: AMIRKABIR INTERNATIONAL JOURNAL OF MODELING, IDENTIFICATION, SIMULATION AND CONTROL Year:2013 | Volume:45 | Issue:2 Page(s): 1-10

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Title

CENTRALIZED CLUSTERING METHOD TO INCREASE ACCURACY IN ONTOLOGY MATCHING SYSTEMS

Author(s)

BABALOU SAMIRA | KARGAR MOHAMMAD JAVAD | DAVARPANAH SEYYED HASHEM

Keywords

ONTOLOGY MATCHING

CLUSTERING METHOD

LARGE-SCALE MATCHING

SEMANTIC GRAPH

Abstract

Ontology is the main infrastructure of the Semantic Web which provides facilities for integration, searching and sharing of information on the web. Development of ontologies as the basis of semantic web and their heterogeneities have led to the existence of ONTOLOGY MATCHING. By emerging large-scale ontologies in real domain, the ONTOLOGY MATCHING systems faced with some problem like memory consumption. Therefore, partitioning the ontology was proposed. In this paper, a new CLUSTERING METHOD for the concepts within ontologies is proposed, which is called SeeCC. The proposed method is a seeding-based CLUSTERING METHOD which reduces the complexity of comparison by using clusters’ seed. The SeeCC method facilitates the memory consuming problem and increases their accuracy in the LARGE-SCALE MATCHING problem as well. According to the evaluation of SeeCC's results with Falcon-AO and the proposed system by Algergawy accuracy of the ONTOLOGY MATCHING is easily observed. Furthermore, compared to OAEI (Ontology Alignment Evaluation Initiative), SeeCC has acceptable result with the top ten systems.

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APA: Copy

BABALOU, SAMIRA, KARGAR, MOHAMMAD JAVAD, & DAVARPANAH, SEYYED HASHEM. (2013). CENTRALIZED CLUSTERING METHOD TO INCREASE ACCURACY IN ONTOLOGY MATCHING SYSTEMS. AMIRKABIR INTERNATIONAL JOURNAL OF MODELING, IDENTIFICATION, SIMULATION AND CONTROL, 45(2), 1-10. SID. https://sid.ir/paper/320024/en

Vancouver: Copy

BABALOU SAMIRA, KARGAR MOHAMMAD JAVAD, DAVARPANAH SEYYED HASHEM. CENTRALIZED CLUSTERING METHOD TO INCREASE ACCURACY IN ONTOLOGY MATCHING SYSTEMS. AMIRKABIR INTERNATIONAL JOURNAL OF MODELING, IDENTIFICATION, SIMULATION AND CONTROL[Internet]. 2013;45(2):1-10. Available from: https://sid.ir/paper/320024/en

IEEE: Copy

SAMIRA BABALOU, MOHAMMAD JAVAD KARGAR, and SEYYED HASHEM DAVARPANAH, “CENTRALIZED CLUSTERING METHOD TO INCREASE ACCURACY IN ONTOLOGY MATCHING SYSTEMS,” AMIRKABIR INTERNATIONAL JOURNAL OF MODELING, IDENTIFICATION, SIMULATION AND CONTROL, vol. 45, no. 2, pp. 1–10, 2013, [Online]. Available: https://sid.ir/paper/320024/en

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