摘要
【目的】探讨属性约简方法的发展趋势及应用领域,为该领域的系统研究提供借鉴。【文献范围】在Web of Science和CNKI中分别以检索词"Attribute Reduction"和"属性约简"进行文献检索,再结合主题筛选,精读并使用追溯法获得属性约简研究的代表性文献共142篇。【方法】介绍属性约简的基本方法,对属性约简方法的主要研究内容进行归类总结。【结果】属性约简方法的热点研究集中在利用粗糙集、粒计算和形式概念分析等基本方法,其发展趋势与数据的动态性、智能算法之间的相互融合密切相关。【局限】仅针对属性约简算法之间的融合发展进行简要论述,未对其进行更深入探讨。【结论】多种属性约简算法的融合研究是属性约简算法的发展趋势。
[Objective]This paper reviews the methods,developing trends and applications of attribute reduction,aiming to support systematic research in this field.[Coverage]From the Web of Science and CNKI,we retrieved142 articles on attribute reduction,using the keywords of"Attribute Reduction"and"属性约简".We also optimized the results with topic selection,intensive reading and retrospective method.[Methods]We surveyed the fundamentals of attribute reduction,and then summarized its leading research.[Results]The popular research of attribute reduction methods focused on rough sets,granular computing and formal concept analysis.Its developing trends were closely related to the dynamics of data and the fusion of intelligent algorithms.[Limitations]We only briefly discussed the merging of attribute reduction algorithms.[Conclusions]We explored the developing trends of attribute reduction methods.
作者
马捷
葛岩
蒲泓宇
Ma Jie;Ge Yan;Pu Hongyu(School of Management,Jilin University,Changchun 130022,China;Center for Information Resources Research,Jilin University,Changchun 130022,China;School of Computer Science and Technology,Beihua University,Jilin 132021,China)
出处
《数据分析与知识发现》
CSSCI
CSCD
北大核心
2020年第1期40-50,共11页
Data Analysis and Knowledge Discovery
基金
国家社会科学基金重点项目“信息生态视角下智慧城市信息协同结构与模式研究”(项目编号:17ATQ007)的研究成果之一。
关键词
粗糙集
粒计算
形式概念分析
Rough Set
Granular Computing
Formal Concept Analysis
