《计算机应用研究》|Application Research of Computers

精简高效用模式挖掘综述

Survey of algorithms for concise high utility pattern mining

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作者 孙蕊,韩萌,张春砚,申明尧,杜诗语
机构 北方民族大学 计算机科学与工程学院,银川 750021
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文章编号 1001-3695(2021)04-003-0975-07
DOI 10.19734/j.issn.1001-3695.2020.02.0092
摘要 全集高效用模式挖掘算法存在的关键问题之一是会产生冗余的高效用项集,这将导致用户很难在大量的高效用项集中发现有用的信息,严重降低了高效用模式挖掘算法的性能。为解决这一问题,衍生出了精简高效用模式挖掘算法,其主要包括最大高效用模式、闭合高效用模式、top-<i>k</i>高效用模式以及三者之间的组合高效用模式挖掘算法等。首先,介绍了精简高效用模式的相关问题描述;然后,从有无候选项集生成、一两阶段挖掘方法、数据结构类型和剪枝策略等角度,重点分类总结了精简高效用模式挖掘方法;最后,给出了精简高效用模式的进一步研究方向,包括处理基于负项的高效用精简模式、处理基于时间的高效用精简模式及处理动态复杂的数据等。
关键词 精简高效用模式挖掘; 最大高效用模式; 闭合高效用模式; top-<;i>;k<;/i>;高效用模式
基金项目 国家自然科学基金资助项目(61563001)
计算机应用技术自治区重点学科资助项目(PY1902)
宁夏自然基金资助项目(NZ17111)
北方民族大学研究生创新项目(YCX19065)
本文URL http://www.arocmag.com/article/01-2021-04-003.html
英文标题 Survey of algorithms for concise high utility pattern mining
作者英文名 Sun Rui, Han Meng, Zhang Chunyan, Shen Mingyao, Du Shiyu
机构英文名 School of Computer Science & Technology,North Minzu University,Yinchuan 750021,China
英文摘要 There is a key problem in the complete set high utility pattern mining algorithms, which is that there are too many redundant high utility itemsets. This makes it difficult for users to find useful information in a large set of high utility itemsets, which seriously reduces the performance of high utility pattern mining algorithms. To solve this problem, it derived a concise high utility pattern mining method, which mainly included the maximal high utility pattern, the closed high utility pattern, the top-<i>k</i> high utility pattern, and the combination high utility pattern mining method among the three. First, this paper introduced the related problem descriptions of concise high utility patterns. Then, from the perspectives of candidate set generation, data structure types, and pruning strategies, the paper summarized concise high utility pattern mining methods. Finally, this paper gave further research directions for concise high utility pattern, including the processing of concise high utility pattern based on negative terms, concise high utility pattern based on time and deal with dynamic and complex data.
英文关键词 concise high utility pattern mining; maximal high utility pattern; closed high utility pattern; top-< i> k< /i> high utility pattern
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收稿日期 2020/2/20
修回日期 2020/4/13
页码 975-981
中图分类号 TP3
文献标志码 A