PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Giannotti F., Nanni M., Pedreschi D., Pinelli F. Mining sequences with temporal annotations. In: ACM Symposium on Applied Computing - Special Track on Data Mining (Dijon, France, 23-27 April 2006). Proceedings, pp. 593 - 597. ACM, 2006.
 
 
Abstract
(English)
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.
Subject Temporal Data Mining
Sequential Patterns
I.2.6 Learning


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