Conceptual Clustering Using Relational Information

Proceedings of the AAAI Conference on Artificial Intelligence, 5

Volume

Science

Learning

Work in conceptual clustering has focused on creating cIasses from objects with a fixed set of features, such as color or size. In this paper we describe a system which uses relations between the objects being clustered as well as features of the objects to form a hierarchy tree of classes. Unlike previous conceptual clustering systems, this algorithm can define new attributes. Using relational information the system is able to find object classifications not possible with conventional conceptual clustering methods.