Semantics-based Information Brokering

Abstract

The rapid advances in computer and communication technologies, and their merger, is leading to a global information market place. It will consist of federations of very large number of information systems that will cooperate to varying extents to support the users' information needs. We discuss an approach to <i>information brokering</i> in the above environment. We discuss two of its tasks: <i>information resource discovery</i>, which identifies relevant information sources for a given query, and <i>query processing</i>, which involves the generation of appropriate mapping from relevant but structurally heterogeneous objects. Query processing consists of <i>information focusing</i> and <i>information correlation</i>. Our approach is based on: <i>semantic proximity</i>, which represents semantic similarities based on the <i>context</i> of comparison, and <i>schema correspondences</i> which are used to represent structural mappings and are associated with the context. The <i>context</i> of comparison of the two objects is the primary vehicle to represent the semantics for determining semantic proximity. Specifically, we use a partial context representation to capture the semantics in terms of the assumptions in the intended <i>use</i> of the objects and the intended <i>meaning</i> of the user query. Information focusing is supported by subsequent context comparison. The same mechanism can be used to support information resource discovery. Context comparison leads to changes in schema correspondences that are used to support information correlation.