A pattern growth-based sequential pattern mining algorithm called prefixSuffixSpan

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 p...

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Bibliographic Details
Published in:EAI endorsed transactions on scalable information systems 2017-01, Vol.4 (12), p.152103-14
Main Authors: Belise, Kenmogne Edith, Calvin, Tadmon, Roger, Nkambou
Format: Article
Language:English
Subjects:
Algorithms
Data mining
partitioning
Pattern analysis
pattern-growth direction
pattern-growth ordering
pruning
search space
sequence mining
sequential pattern
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Summary: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.
ISSN:2032-9407
2032-9407
DOI:10.4108/eai.18-1-2017.152103