A unified and flexible framework for comparing simple and complex patterns

Authors:
Ilaria Bartolini;Paolo Ciaccia;Irene Ntoutsi;Marco Patella;Yannis Theodoridis
Affiliations:
DEIS - IEIIT/BO-CNR, University of Bologna, Italy;DEIS - IEIIT/BO-CNR, University of Bologna, Italy;Research Academic Computer Technology Institute, Athens, Greece, and Department of Informatics, University of Piraeus, Greece;DEIS - IEIIT/BO-CNR, University of Bologna, Italy;Research Academic Computer Technology Institute, Athens, Greece, and Department of Informatics, University of Piraeus, Greece
Venue:
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Year:
2004

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Abstract

One of the most important operations involving Data Mining patterns is computing their similarity. In this paper we present a general framework for comparing both simple and complex patterns, i.e., patterns built up from other patterns. Major features of our framework include the notion of structure and measure similarity, the possibility of managing multiple coupling types and aggregation logics, and the recursive definition of similarity for complex patterns.