Abstract
An enormous proliferation of computer technology in modern societies has produced a severe information overload. The navigation through the masses of available information in order to derive desired knowledge is becoming increasingly difficult. This creates a demand for intelligent systems capable of assisting data analysts in extracting goal-oriented knowledge from large volumes of data. This paper presents a multistrategy methodology and a system, INLEN, for knowledge discovery in large relational databases. The system integrates data base, knowledge base and machine learning technologies. It offers a data analyst an integrated interface and a wide range of knowledge generation operators, as described in the Inferential Theory of Learning. Presented ideas are illustrated by results from experiments with INLEN.
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