A Multi-relational Rule Discovery System

This paper describes a rule discovery system that has been developed as part of an ongoing research project. The system allows discovery of multirelational rules using data from relational databases. The basic assumption of the system is that objects to be analyzed are stored in a set of tables. Multirelational rules discovered would either be used in predicting an unknown object attribute value, or they can be used to see the hidden relationship between the objects’ attribute values. The rule discovery system, developed, was designed to use data available from any possible ‘connected’ schema where tables concerned are connected by foreign keys. In order to have a reasonable performance, the ‘hypotheses search’ algorithm was implemented to allow construction of new hypotheses by refining previously constructed hypotheses, thereby avoiding the work of re-computing.