Abstract
Mining frequent patterns has been studied popularly in data mining research. All of previous studies assume that items in a pattern are unordered. However, the order existing between items must be considered in some applications. In this paper, we first give the formal model of ordered patterns and discuss the problem of mining frequent ordered patterns. Base on our analyses, we present two efficient algorithms for mining frequent ordered patterns. We also present results of applying these algorithms to a synthetic data set, which show the effectiveness of our algorithms. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Deng, Z. H., Ji, C. R., Zhang, M., & Tang, S. W. (2005). Mining frequent ordered patterns. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3518 LNAI, pp. 150–154). Springer Verlag. https://doi.org/10.1007/11430919_19
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