Ontology-based Induction of High Level Classification Rules

Abstract

A tool that could be beneficial to the data mining community is one that facilitates the seamless integration of knowledge bases and databases. This kind of tool could form the foundation of a data mining system capable of finding interesting information using ontologies. In this paper, we describe a new algorithm based on the query facilities provided by such a tool, ParkaDB which is a knowledge representation system. Ontologies and relational databases are merged thus extending the range of queries that can be issued against databases. This extended query capability makes it possible to generalize from low-level concepts to high-level concepts on demand. Given this extended querying capability, we are developing a classification algorithm that will find classification rules at multiple levels of abstraction.