Multi-relational data mining, using UML for ILP

Abstract

Although there is a growing need for multi-relational data mining solutions in KDD, the use of obvious candidates from the field of Inductive Logic Programming (ILP) has been limited. In our view this is mainly due to the variation in ILP engines, especially with respect to input specification, as well as the limited attention for relational database issues. In this paper we describe an approach which uses UML as the common specification language for a large range of ILP engines. Having such a common language will enable a wide range of users, including non-experts, to model problems and apply different engines without any extra effort. The process involves transformation of UML into a language called CDBL, that is then translated to a variety of input formats for different engines.