Ontology-based agent community for information integration system in semantic web

The phenomenal growth in recent years of distributed, network, and dynamic information sources remains a significant challenge. Only ontology based approach to this problem resolved heterogeneity, if all the data owners agree to use a common ontology. However, if information is sought from a subset of the participating data sources, there may be concepts common to the subset that are not included in the full common ontology, and therefore are unavailable for information sharing. Therefore, a novel ontology-based agent community approach is developed for agents, which generates the largest intersection of shared data across any selected subset of data sources. This paper proposes ontology-based agent community approach for information integration system that demonstrates a flexible and dynamic approach for the fusion of data across combinations of participating heterogeneous data sources to maximize information sharing by dynamically generating common ontology over the data sources of interest.