A Large Scale Multi-objective Ontology Matching Framework

  • Xingsi XueEmail author
  • Aihong Ren
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 81)


Multi-Objective Evolutionary Algorithm (MOEA) is emerging as a state-of-the-art methodology to solve the ontology meta-matching problem. However, the huge search scale of large scale ontology matching problem stops MOEA based ontology matching technology from correctly and completely identifying the semantic correspondences. To this end, in this paper, a large scale multi-objective ontology matching framework is proposed, which works with three sequential steps: (1) partition the large scale ontologies into similar ontology segment pairs; (2) utilize MOEA to match the similar ontology segments in parallel; (3) select the representative ontology segment alignments, which are further aggregated to obtain the final ontology alignment. In addition, a novel multi-objective model is also constructed for ontology matching problem and the MOEA and entity similarity measure that could be used in this framework are also recommended. The experimental result shows the effectiveness of our proposal.


Multi-Objective Evolutionary Algorithm Large scale ontology matching Ontology partition 



This work is supported by the National Natural Science Foundation of China (No. 61503082), Natural Science Foundation of Fujian Province (No. 2016J05145), Scientific Research Startup Foundation of Fujian University of Technology (No. GY-Z15007), Fujian Province outstanding Young Scientific Researcher Training Project (No. GY-Z160149) and China Scholarship Council.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.College of Information Science and EngineeringFujian University of TechnologyFuzhouChina
  2. 2.Fujian Provincial Key Laboratory of Big Data Mining and ApplicationsFujian University of TechnologyFuzhouChina
  3. 3.Department of MathematicsBaoji University of Arts and SciencesBaojiChina

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