Document Type

Report

Publication Date

10-1993

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 propose an architecture which may facilitate meeting these needs. It consists of three main components: information providers, information brokers and information consumers. We also propose an approach to information brokering. We discuss two of it's tasks: information resource discovery, which identities relevant information sources for a given query, and query processing, which involves the generation of appropriate mapping from relevant but structurally heterogeneous objects. Query processing consists of information focusing and information correlation.

While the access-based search, and syntactic and hierarchical information organization has been adequate in the past, information brokering in presence of huge digital libraries or millions of information sources will likely require semantics and information-content based search and structuring of information. Our approach is based on: semantic proximity, which represents semantic similarities based on the context of comparison, and schema correspondences which are used to represent structural mappings and are associated with the context. The context of comparison of the two objects is the primary vehicle to represent the semantics for determining semantic proximity. Specifically, we use a context to capture the semantics in terms of the meaning and/or the use of an object. Using a partial context representation, we capture the assumptions in the intended use of the objects and the intended meaning 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.

Comments

Rutgers University Department of Computer Science Technical Report DCS-TR-301

Download


Share

COinS