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 ag-gregation logics, and the recursive definition of similarity for complex patterns.
Bartolini I, Ciaccia P, Ntoutsi I, Patella M, Theodoridis Y. (2004). A Unified and Flexible Framework for Comparing Simple and Complex Patterns. BERLIN : Springer.
A Unified and Flexible Framework for Comparing Simple and Complex Patterns
BARTOLINI, ILARIA;CIACCIA, PAOLO;PATELLA, MARCO;
2004
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 ag-gregation logics, and the recursive definition of similarity for complex patterns.File in questo prodotto:
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