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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CITATION STYLE
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9423, pp. 643–650). Springer Verlag. https://doi.org/10.1007/978-3-319-25751-8_77
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