A pattern growth-based sequential pattern mining algorithm called prefixSuffixSpan

• Main Authors: Kenmogne Edith Belise, Tadmon Calvin, Nkambou Roger
• Format: Article
• Language: English
• Published: European Alliance for Innovation (EAI) 2017-01-01
• Series: EAI Endorsed Transactions on Scalable Information Systems
• Subjects: sequence mining; sequential pattern; pattern-growth direction; pattern-growth ordering; search space; pruning; partitioning
• Online Access: http://eudl.eu/doi/10.4108/eai.18-1-2017.152103

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.