A Clustering-Based Approach for Large-Scale Ontology Matching [chapter]

Alsayed Algergawy, Sabine Massmann, Erhard Rahm
2011 Lecture Notes in Computer Science  
Schema and ontology matching have attracted a great deal of interest among researchers. Despite the advances achieved, the large matching problem still presents a real challenge, such as it is a timeconsuming and memory-intensive process. We therefore propose a scalable, clustering-based matching approach that breaks up the large matching problem into smaller matching problems. In particular, we first introduce a structure-based clustering approach to partition each schema graph into a set of
more » ... sjoint subgraphs (clusters). Then, we propose a new measure that efficiently determines similar clusters between every two sets of clusters to obtain a set of small matching tasks. Finally, we adopt the matching prototype COMA++ to solve individual matching tasks and combine their results. The experimental analysis reveals that the proposed method permits encouraging and significant improvements.
doi:10.1007/978-3-642-23737-9_30 fatcat:zku6egpckbdwtbev227rj7lc7y