南京师大学报（自然科学版）2025，Vol.48Issue(2)：124-138,15.DOI:10.3969/j.issn.1001-4616.2025.02.013
象群优化的高效用项集挖掘算法
Elephant Herding Optimization Algorithm for Mining High Utility Itemsets
摘要
Abstract
Heuristic high utility itemset mining is an active research topic in the field of data mining in recent years.To solve the problem of itemset loss caused by the early convergence of heuristic high utility itemset mining algorithms,a new algorithm is designed to discovering more high utility itemsets within fewer iterations.The proposed strategy of positional evolution based on the female elephant factor is proposed to reduce effectively the search space and improve the execution efficiency of the algorithm.Moreover,in order to prevent the algorithm from converging too quickly and falling into local optimum,the proposed strategy of two-phase population diversity maintenance which keeps a balance between population diversity and convergence.Extensive experiments on real datasets show that the proposed algorithm outperforms the advanced heuristic high utility mining algorithms.关键词
高效用项集挖掘/启发式算法/象群优化/进化策略/多样性维护策略Key words
high utility itemset mining/heuristic algorithms/elephant herding optimization/evolution strategy/population diversity maintenance strategy分类
计算机与自动化引用本文复制引用
何菲菲,韩萌,张瑞华,李春鹏,孟凡兴..象群优化的高效用项集挖掘算法[J].南京师大学报（自然科学版）,2025,48(2):124-138,15.基金项目
国家自然科学基金项目(62062004)、宁夏自然科学基金项目(2023AAC03315)、北方民族大学中央高校基本科研业务费专项资金资助项目(2021KJCX10)、北方民族大学研究生创新项目(YCX24124). （62062004）
