Ontology-based semantic matching in distributed Active data warehouse

Along with the development and population of network, data sources' heterogeneities gradually become a crucial problem. So the need of resolving these heterogeneities is becoming more important, especially semantic heterogeneities. Two data sources often have the different words to describe the same meaning or the same word to present the different meanings. Despite the critical importance, current approaches to semantic matching of heterogeneous databases have not been sufficiently effective. This paper uses ontology technology to get the semantic matching in distributed active data warehouse. Our approach aims at creating ontologies and measuring semantic similarities among concepts presented in different ontologies. Then a process of whole similarity matching is presented and validated. From this method, the precision which describes how much semantic heterogeneity can be resolved between two data sources is higher than other way.