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.
This work was supported by the European Commission under the IST-2001-33058 Thematic Network. PANDA ”PAtterns for Next-generation DAtabase systems” (2001-04).
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Bartolini, I., Ciaccia, P., Ntoutsi, I., Patella, M., Theodoridis, Y. (2004). A Unified and Flexible Framework for Comparing Simple and Complex Patterns. In: Boulicaut, JF., Esposito, F., Giannotti, F., Pedreschi, D. (eds) Knowledge Discovery in Databases: PKDD 2004. PKDD 2004. Lecture Notes in Computer Science(), vol 3202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30116-5_45
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DOI: https://doi.org/10.1007/978-3-540-30116-5_45
Publisher Name: Springer, Berlin, Heidelberg
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