[1]陆 悠,华 泽,奚雪峰,等.一种面向增删操作的粗糙集属性约简更新算法[J].南京师大学报(自然科学版),2015,38(01):48.
　Lu You,Hua Ze,Xi Xuefeng,et al.An Attribute Reduction Update Algorithm for Object’sAdding-Deleting Based on Rough Set Theory[J].Journal of Nanjing Normal University(Natural Science Edition),2015,38(01):48.
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一种面向增删操作的粗糙集属性约简更新算法()
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《南京师大学报》（自然科学版）[ISSN:1001-4616/CN:32-1239/N]

卷:
第38卷
期数:
2015年01期
页码:
48
栏目:
计算机科学
出版日期:
2015-06-30

文章信息/Info

Title:
An Attribute Reduction Update Algorithm for Object’sAdding-Deleting Based on Rough Set Theory
作者:
陆 悠; 华 泽; 奚雪峰; 张 妮; 吴宏杰
苏州科技学院电子与信息工程学院,江苏 苏州 215000
Author(s):
Lu You; Hua Ze; Xi Xuefeng; Zhang Ni; Wu Hongjie
School of Electronical and Information Engineering,Suzhou University of Science and Technology,Suzhou 215000,China
关键词:
粗糙集; 增量式数据挖掘; 属性约简
Keywords:
rough set; incremental data mining; reduction of attribute
分类号:
TP18
文献标志码:
A
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.
Abstract:
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.

参考文献/References:

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[3]Jia 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,等. 面向网络状态的自适应用户行为评估方法[J]. 通信学报,2013(7):71-80.
[5]钱文彬,杨炳儒,徐章艳. 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.
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备注/Memo

备注/Memo:
收稿日期:2014-08-16.
基金项目:江苏省自然科学基金(BK20131154).
通讯联系人:陆悠,博士生,讲师,研究方向:网络应用及安全,用户行为控制. E-mail:luyou. china@gmail. Com
更新日期/Last Update: 2015-03-30