Ontology matching has played a great role in many well-known applications. It can identify the elements corresponding to each other. At present, with the rapid development of ontology applications, domain ontologies became very large in scale. Solving large scale ontology matching problems is beyond the reach of the existing matching methods. To improve this situation a modularization-based approach (called MOM) was proposed in this paper. It tries to decompose a large matching problem into several smaller ones and use a method to reduce the complexity dramatically. Several large and complex ontologies have been chosen and tested to verify this approach. The results show that the MOM method can significantly reduce the time cost while keeping the high matching accuracy. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Wang, Z., Wang, Y., Zhang, S., Shen, G., & Du, T. (2006). Matching large scale ontology effectively. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4185 LNCS, pp. 99–105). Springer Verlag. https://doi.org/10.1007/11836025_10
Mendeley helps you to discover research relevant for your work.