In this paper we propose an extension of the sequence mining paradigm to (temporally-) annotated sequential patterns, where each transition in a sequential pattern is annotated with a typical transition time derived from the source data. Then, we present a basic solution for the novel mining problem based on the combination of sequential pattern mining and clustering, and assess this solution on two realistic datasets, illustrating how potentially useful patterns of the new form are extracted. Copyright 2006 ACM.

Mining sequences with temporal annotations

Nanni M.;Pinelli F.
2006-01-01

Abstract

In this paper we propose an extension of the sequence mining paradigm to (temporally-) annotated sequential patterns, where each transition in a sequential pattern is annotated with a typical transition time derived from the source data. Then, we present a basic solution for the novel mining problem based on the combination of sequential pattern mining and clustering, and assess this solution on two realistic datasets, illustrating how potentially useful patterns of the new form are extracted. Copyright 2006 ACM.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11771/23958
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