Tao Li1, Yongzhen Ren1, *, Yongjun Ren2, Jinyue Xia3
CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 337-354, 2020, DOI:10.32604/cmc.2020.06462
Abstract Apriori algorithm is often used in traditional association rules mining, searching
for the mode of higher frequency. Then the correlation rules are obtained by detected the
correlation of the item sets, but this tends to ignore low-support high-correlation of
association rules. In view of the above problems, some scholars put forward the positive
correlation coefficient based on Phi correlation to avoid the embarrassment caused by
Apriori algorithm. It can dig item sets with low-support but high-correlation. Although the
algorithm has pruned the search space, it is not obvious that the performance of the running
time based on the big data… More >
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