Graph-Based Hierarchical Conceptual Clustering

May 2000

Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2000)

Volume

Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2000)

All Papers

Hierarchical conceptual clustering has been proven to be a useful data mining technique. Graph-based representation of structural information has been shown to be successful in knowledge discovery. The Subdue substructure discovery system provides the advantages of both approaches. In this paper we present Subdue and focus on its clustering capabilities. We use two examples to illustrate the validity of the approach both in structured and unstructured domains, as well as compare Subdue to an earlier clustering algorithm.