Knowledge Discovery from Multiple Databases

James S. Ribeiro, Kenneth A. Kaufman, and Larry Kerschberg, George Mason University

Knowledge discovery systems for databases are employed to provide valuable insights into characteristics and relationships that may exist in the data, but are unknown to the user. This paper describes a methodology and system for performing knowledge discovery across multiple databases. These enhancements have been integrated into the prototype knowledge discovery system called INLEN. The enhancements include the incorporation of primary and foreign keys as well as the development and processing of knowledge segments.

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