Resource and Knowledge Discovery in Global Information Systems: A Scalable Multiple Layered Database Approach

With huge amounts of information connected to the global information network (Internet), e cient and e ective discovery of resource and knowledge from the \global information base" has become an imminent research issue, especially with the advent of the Information SuperHighway. In this article, a multiple layered database (MLDB) approach is proposed to handle the resource and knowledge discovery in global information base. A multiple layered database is a database formed by generalization and transformation of the information, layer-by-layer, starting from the original information base (treated as layer-0, the primitive layer). Information retrieval, data mining, and data analysis techniques can be used to extract and transform information from a lower layer database to a higher one. Layer-1 and higher layers of an MLDB can be modeled by an extended-relational or object-oriented model, constructed automatically, and updated incrementally. Information at all the layers except the primitive one can be stored, managed and retrieved by the available database technology; resources can be found by controlled search through di erent layers of the database; and knowledge discovery can be performed e ciently in such a multiple layered database.