Cluster-based similarity aggregation for ontology matching

Cluster-based similarity aggregation (CSA) is an automatic similarity aggregating system for ontology matching. The system have two main part. The first is calculation and combination of different similarity measures. The second is extracting alignment. The system first calculates five different basic measures to create five similarity matrixes, i.e, string-based similarity measure, WordNet-based similarity measure... Furthermore, it exploits the advantage of each measure through a weight estimation process. These similarity matrixes are combined into a final similarity matrix. After that, the pre-alignment is extracted from this matrix. Finally, to increase the accuracy of the system, the pruning process is applied.