重庆工商大学学报（自然科学版）2026，Vol.43Issue(3)：99-107,9.DOI:10.16055/j.issn.1672-058X.2026.0003.012
基于注意力机制的高效关联规则算法
An Efficient Association Rule Algorithm Based on Attention Mechanism
摘要
Abstract
Objective Aiming at the large amount of redundancy generated during the mining process of frequent item sets in datasets with high similarity and frequent occurrence among transactions,this paper analyzes the deficiencies of some existing association rule algorithms in mining frequent item sets and proposes an association rule mining algorithm that uses an attention mechanism for pruning.Methods This algorithm combined the advantages of the vertical data format and the attention mechanism.It sequentially calculated the attention weights in frequent k-item sets,used these weights to filter out the redundancy in intersection calculations,generated simplified frequent item sets,and finally merged the simplified frequent item sets with the attention weights to obtain the frequent item sets.Results The experimental results showed that on the Data dataset,the proposed algorithm improved time efficiency by up to 94.6％,73.0％,and 95.5％compared with Eclat,Apriori,and FP-Growth,respectively;it also saved up to 61.991 MB of space compared with FP-Growth.On the Accident dataset,it achieved maximal time efficiency improvements of 93.4％,69.0％,and 85.7％over the same three baselines,respectively,with a maximum space saving of 58.786 MB against FP-Growth.Conclusion By introducing the attention mechanism,the generalization ability and stability of the algorithm are enhanced,the redundancy generated during frequent item set mining is reduced,the algorithm speed is improved,and the memory overhead during the mining process is lowered.Especially for datasets with a large AFI index and low support,this algorithm has more advantages in terms of time and space consumption.关键词
关联规则/频繁项集/冗余/注意力机制/精简频繁项集Key words
association rule/frequent item set/redundancy/attention mechanism/simplified frequent item set分类
信息技术与安全科学引用本文复制引用
管博伦,张立平,董伟,李闰枚,朱静波,孔娟娟,汪焱..基于注意力机制的高效关联规则算法[J].重庆工商大学学报（自然科学版）,2026,43(3):99-107,9.基金项目
国家自然基金面上项目资助(32171888). （32171888）
