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

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.

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