Traditional association rules mining cannot meet the demands arising from some real applications. By considering the different values of individual items as utilities, utility mining focuses on identifying the itemsets with high utilities. In this paper, we present a Two-Phase algorithm to efficiently prune down the number of candidates and precisely obtain the complete set of high utility itemsets. It performs very efficiently in terms of speed and memory cost both on synthetic and real databases, even on large databases that are difficult for existing algorithms to handle. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Liu, Y., Liao, W. K., & Choudhary, A. (2005). A two-phase algorithm for fast discovery of high utility itemsets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3518 LNAI, pp. 689–695). Springer Verlag. https://doi.org/10.1007/11430919_79
Mendeley helps you to discover research relevant for your work.