The application of existing ontology aligning technologies based on evolutionary algorithm is limited by the huge search space of large scale ontology aligning problem. To this end, in this paper, a large scale ontology aligning approach based on a fast elitist Non-dominated Sorting Genetic Algorithm for multi-objective optimization (NSGA-Ⅱ) was proposed. To be specific, it worked in three steps: 1) a neighbor similarity based ontology partitioning algorithm was presented to split the source ontology into a set of disjoint concept blocks; 2) a relevant concept filtering method was proposed to determine the concept block in target ontology associated with each source one; 3) NSGA-Ⅱ was utilized to align the various concept block pairs and a greedy algorithm was used to aggregate various results. Small scale bibliographic ontology benchmark and large scale biomedic ontology benchmark in OAEI 2012 were used to test the proposed approach. The comparisons with the participants of OAEI 2012 show that the large scale ontology aligning approach based on NSGA-Ⅱ is able to determine good alignments in a short time, and therefore it is effective.
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2014, Vol. 34 
