Towards semantic-driven, flexible and scalable framework for peering and querying e-catalog communities

Given that e-catalogs are often autonomous and heterogeneous, effectively integrating and querying them is a delicate and time-consuming task. More importantly, the number of e-catalogs to be integrated and queried may be large and continuously changing. Conventional approaches where the development of an integrated e-catalog requires the understanding of each of the underlying catalog are inappropriate. In this paper, we use the concept of e-catalog communities and peer relationships among them to facilitate the querying of a potentially large number of dynamic e-catalogs. E-catalog communities are essentially containers of related e-catalogs. We propose a flexible and user-centric query matching algorithm that exploits both community descriptions and peer relationships to find e-catalogs that best match a user query. The user query is formulated using a description of a given community.