Abstract
In this paper, we propose a novel algorithm for mining frequent sequences, called SPaMi-FTS (Sequential Pattern Mining based on Frequent Two-Sequences). SPaMi-FTS introduces a new data structure to store the frequent sequences, which together with a new pruning strategy to reduce the number of candidate sequences and a new heuristic to generate them, allows to increase the efficiency of the frequent sequence mining. The experimental results show that the SPaMi-FTS algorithm has better performance than the main algorithms reported to discover frequent sequences.
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Febrer-Hernández, J.K., Hernández-Palancar, J., Hernández-León, R., Feregrino-Uribe, C. (2014). SPaMi-FTS: An Efficient Algorithm for Mining Frequent Sequential Patterns. In: Bayro-Corrochano, E., Hancock, E. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2014. Lecture Notes in Computer Science, vol 8827. Springer, Cham. https://doi.org/10.1007/978-3-319-12568-8_58
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DOI: https://doi.org/10.1007/978-3-319-12568-8_58
Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-12568-8
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