In this paper we address an extension of the sequential pattern mining problem which aims at detecting the significant differences between frequent sequences with respect to given classes. The resulting problem is known as contrast sequential pattern mining, since it merges the two notions of sequential pattern and contrast pattern. For this problem we present a declarative approach based on Answer Set Programming (ASP). The efficiency and the scalability of the ASP encoding are evaluated on two publicly available datasets, iPRG and UNIX User, by varying parameters, also in comparison with a hybrid ASP-based approach.

Mining Contrast Sequential Patterns with ASP

Lisi F. A.;Sterlicchio G.
2023-01-01

Abstract

In this paper we address an extension of the sequential pattern mining problem which aims at detecting the significant differences between frequent sequences with respect to given classes. The resulting problem is known as contrast sequential pattern mining, since it merges the two notions of sequential pattern and contrast pattern. For this problem we present a declarative approach based on Answer Set Programming (ASP). The efficiency and the scalability of the ASP encoding are evaluated on two publicly available datasets, iPRG and UNIX User, by varying parameters, also in comparison with a hybrid ASP-based approach.
2023
9783031475450
9783031475467
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/460122
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