Abstract
In this paper, we propose a novel algorithm for mining Sequential Patterns-based Rules, called SPaR-FTR. This algorithm introduces a new efficient strategy to generate the set of sequential rules based on the interesting rules of size three. The experimental results show that the SPaR-FTR algorithm has better performance than the main algorithms reported to discover frequent sequences, all they adapted to mine this kind of sequential rules.
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Febrer-Hernández, J.K., Hernández-León, R., Hernández-Palancar, J., Feregrino-Uribe, C. (2015). SPaR-FTR: An Efficient Algorithm for Mining Sequential Patterns-Based Rules. In: Pardo, A., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2015. Lecture Notes in Computer Science(), vol 9423. Springer, Cham. https://doi.org/10.1007/978-3-319-25751-8_77
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DOI: https://doi.org/10.1007/978-3-319-25751-8_77
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