A pattern growth-based sequential pattern mining algorithm called prefixSuffixSpan

Authors

  • Kenmogne Edith Belise LIFA
  • Tadmon Calvin LIFA
  • Nkambou Roger University of Quebec at Montreal image/svg+xml

DOI:

https://doi.org/10.4108/eai.18-1-2017.152103

Keywords:

sequence mining, sequential pattern, pattern-growth direction, pattern-growth ordering, search space, pruning, partitioning

Abstract

Sequential pattern mining is an important data mining problem widely addressed by the data mining community, with a very large field of applications. The sequence pattern mining aims at extracting a set of attributes, shared across time among a large number of objects in a given database. The work presented in this paper is directed towards the general theoretical foundations of the pattern-growth approach. It helps indepth understanding of the pattern-growth approach, current status of provided solutions, and direction of research in this area. In this paper, this study is carried out on a particular class of pattern-growth algorithms for which patterns are grown by making grow either the current pattern prefix or the current pattern suffix from the same position at each growth-step. This study leads to a new algorithm called prefixSuffixSpan. Its correctness is proven and experimentations are performed.

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Published

19-01-2017

How to Cite

1.
Edith Belise K, Calvin T, Roger N. A pattern growth-based sequential pattern mining algorithm called prefixSuffixSpan. EAI Endorsed Scal Inf Syst [Internet]. 2017 Jan. 19 [cited 2024 Nov. 25];4(12):e4. Available from: https://publications.eai.eu/index.php/sis/article/view/2247