Much academic research has been conducted about the process of association rule mining.
More effort is now required for practical application of association rules in various …

Association rule mining is a well-known methodology to discover significant and apparently
hidden relations among attributes in a subspace of instances from datasets. Genetic …

In the single machine environment, the problems of Apriori and FP-Growth algorithm in large-
scale data association rules mining are high memory consumption, low computing …

In real-world applications, transactions usually consist of quantitative values. Many fuzzy
data mining approaches have thus been proposed for finding fuzzy association rules with …

Many fuzzy data mining approaches have been proposed for finding fuzzy association rules
with the predefined minimum support from quantitative transaction databases. Since each …

In this paper, we present a sparse memory allocation data structure for sequential and
parallel data mining. We explored three algorithms utilizing the proposed data structure …

In the modern digital world, online shopping becomes essential in human lives. Online
shopping stores like Amazon show up the" Frequently Bought Together" for their customers …

Frequent pattern mining has been playing an essential role in knowledge discovery and
data mining tasks that try to find usable patterns from databases. Efficiency is especially …

.#/# 现实量化#+ 应用中, 传统的模4 数据ST 算法UU 需要! 对¤ 定的量化#+ 设定最小V 持度W
值, 然而, 这些方法中存在的普X 问题是Y7Z 到合适的最小V 持度W 值, 并且因为推导出的规则 …

Compared to corpora-based machine translation methods, rule-based methods have
deficiencies, which make them unattractive for the researchers of this field. The first problem …