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.

Mining sequences with temporal annotations

Giannotti F;Nanni M;
2006

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.
2006
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
1-59593-108-2
Temporal Data Mining
Sequential Patterns
File in questo prodotto:
File Dimensione Formato  
prod_91345-doc_130352.pdf

solo utenti autorizzati

Descrizione: Mining sequences with temporal annotations
Tipologia: Versione Editoriale (PDF)
Dimensione 174.15 kB
Formato Adobe PDF
174.15 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/62255
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact