Discovering frequent item sets is a key problem in data mining association rules. In this paper, there is a celerity association rules method based on data sort search. Using the plenitude and call terms of frequent item sets, the method efficiency can be improved greatly for the searching time won't increase as the number of item set of the data does, moreover the data can be found by searching the database within 3 times. Using the change between the frequent item sets and standby item sets, the data celerity renew and the min-sup renew can be true. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Huang, Z., & Liao, Q. (2006). A celerity association rules method based on data sort search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3613 LNAI, pp. 1063–1066). Springer Verlag. https://doi.org/10.1007/11539506_131
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