Revisiting "An Apriori-based Approach for First-Order Temporal Pattern Mining"

Authors

  • Sandra de Amo Universidade Federal de Uberlândia
  • Daniel A. Furtado Universidade Federal de Uberlândia
  • Arnaud Giacometti Université de Tours
  • Dominique Laurent ETIS-CNRS-ENSEA-Université de Cergy Pontoise

DOI:

https://doi.org/10.5753/jidm.2010.943

Abstract


A lot of different approaches related to sequential pattern mining have been proposed in the literature,
since 2004, when the original paper was published in the proceedings of SBBD 2004. Among these
approaches, we distinguish five main directions of research: (1) development of more efficient methods
for the classical sequential pattern mining problem, (2) sequential pattern mining with constraints, (3)
multidimensional and multilevel sequential patterns, (4) temporal patterns specified by more general
structures (tree and graph patterns), (5) temporal relational patterns with interval time attributes.

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Author Biographies

Sandra de Amo, Universidade Federal de Uberlândia

Faculdade de Computação

Associate Professor

Daniel A. Furtado, Universidade Federal de Uberlândia

Faculdade de Engenharia Elétrica

PhD Student

Arnaud Giacometti, Université de Tours

LI- Université de Tours UFR de Sciences

Professor

Dominique Laurent, ETIS-CNRS-ENSEA-Université de Cergy Pontoise

Université de Cergy Pontoise

Professor

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Published

2010-05-27

How to Cite

de Amo, S., Furtado, D. A., Giacometti, A., & Laurent, D. (2010). Revisiting "An Apriori-based Approach for First-Order Temporal Pattern Mining". Journal of Information and Data Management, 1(1), 71. https://doi.org/10.5753/jidm.2010.943

Issue

Section

Regular Papers