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一种面向增删操作的粗糙集属性约简更新算法 被引量:2

An Attribute Reduction Update Algorithm for Object's Adding-Deleting Based on Rough Set Theory
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摘要 属性约简是粗糙集理论的核心内容之一,在信息系统的对象信息不断出现增删等更新操作的环境下,如何进行快速有效的属性约简则是一个亟需解决的迫切问题.提出一种面向增删操作的属性约简更新算法,面向更新前后的决策表,首先分析了对象信息动态增加与删除情况下信息熵的变化机制以及约简属性对新增或删除对象的区分情况,然后提出基于区分情况的新条件熵值的计算方法,最后给出基于散列表的属性约简更新算法.实验结果证明,本文方法可以快速求解出增删更新后的属性约简结果,其性能较传统方法有较大优势. Attribute reduction is one of the important topics in the research on rough set theory. When an object was added to or deleted from the original decision table,how to calculate attribute reduction fast and effectively is a pressing problem. This paper proposed an attribute reduction update algorithm. Firstly,the changing mechanism of conditional entropy was analyzed when object is added to or removed from the table,and then we divided the added or removed objects into different cases. Furthermore,we presented the update algorithm based on these cases and implemented it based on hash table. Experiment results show that our algorithm can calculate the attribute reduction fast and outperforms the existing methods.
出处 《南京师大学报(自然科学版)》 CAS CSCD 北大核心 2015年第1期48-56,65,共10页 Journal of Nanjing Normal University(Natural Science Edition)
基金 江苏省自然科学基金(BK20131154)
关键词 粗糙集 增量式数据挖掘 属性约简 rough set incremental data mining reduction of attribute
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  • 1Kim H, Claffy K, Fomenkov M, et al. Intemet traffic classification demystified : myths, caveats, and the best practices [ C ]// Proceedings of ACM CoNEXT'08. New York,2008:l-12.
  • 2Zhang D, Qiu J, Li X. Attribute reduction based on equivalence classes with multiple decision values in rough set [ C ]//Proceed- ings of the International Conference on Information Engineering and Applications ( IEA ) 2012. London: Springer, 2013 : 505- 512.
  • 3Jia X, Tang Z, Liao W, et al. On an optimization representation of decision-theoretic rough set model [ J ]. International Journal of Approximate Reasoning, 2014,55 ( 1 ) : 156-166.
  • 4陆悠,罗军舟,李伟,于枫,夏怒.面向网络状态的自适应用户行为评估方法[J].通信学报,2013,34(7):71-80. 被引量:9
  • 5钱文彬,杨炳儒,徐章艳,张长胜.基于信息熵的核属性增量式高效更新算法[J].模式识别与人工智能,2013,26(1):42-49. 被引量:13
  • 6Janusz A, Slezak D. Rough set methods for attribute clustering and selection [ J ]. Applied Artificial Intelligence, 2014,28 (3) : 220-242.
  • 7Thangavel K,Pethalakshmi A. Dimensionality reduction based on rough set theory:a review [ J ]. Applied Soft Computing, 2009,9(1) :1-12.
  • 8林俊伟,叶东毅.基于邻域辨识矩阵的属性约简增量式算法[J].计算机应用,2009,29(B06):119-121. 被引量:9
  • 9Hu F,Wang G Y, Huang H, et al. Incremental attribute reduction based on element arysets [ C]//Proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Regina ,2005:183-193.
  • 10梁吉业,魏巍,钱宇华.一种基于条件熵的增量核求解方法[J].系统工程理论与实践,2008,28(4):81-89. 被引量:13

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