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On efficient methods of computing attribute-value blocks in incomplete decision systems

文献类型：期刊论文

作者Meng, Zuqiang1,2; Gan, Qiuling1,2; Shi, Zhongzhi3
刊名KNOWLEDGE-BASED SYSTEMS
出版日期2016-12-01
卷号113页码:171-185
关键词Attribute-value block Efficiency Incomplete decision system Rough set theory Missing value Attribute reduction
ISSN号0950-7051
DOI10.1016/j.knosys.2016.09.025
英文摘要In rough set models, almost all computations, such as attribute reduction, rule reduction, etc., are based on attribute-value blocks. Computing attribute-value blocks is most frequently used and time-consuming basic operation for these computations. However, special studies were relatively little reported on the construction of efficient methods of computing attribute-value blocks for incomplete decision systems. In this paper, we considered two representative interpretations of missing values: "do not care" conditions and "lost values", and divided incomplete decision systems into two categories: ones containing only "do not care" conditions and the other ones containing both "do not care" conditions and "lost values", which lead to two kinds of rough set models, tolerance relation-based rough set models (TRRSMs) and characteristic relation-based rough set models (CRRSMs), respectively. Then, two algorithms, division algorithm and index algorithm, for computing attribute-value blocks were proposed, with the division algorithm for TRRSMs and the index algorithm for both CRRSMs and TRRSMs. The two proposed algorithms are far more efficient than usual algorithms when dealing with "do not care" conditions; the division algorithm is a little more efficient than the index algorithm when missing value degrees are small, but it can not deal with "lost values", whereas the index algorithm is evidently more efficient than the division algorithm when missing value degrees are relatively large, and it is relatively insensitive to missing value degrees. Experimental results also show that the proposed algorithms are effective and efficient. Thus, the two proposed methods constitute an effective solution to the problem of efficiently computing attribute-value blocks for incomplete decision systems. (C) 2016 Elsevier B.V. All rights reserved.
资助项目National Natural Science Foundation of China[61363027] ; Guangxi Natural Science Foundation, China[2015GXNSFAA139292] ; National Basic Research Programme of China[2013CB329502]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000387519500015
出版者ELSEVIER SCIENCE BV
源URL[http://119.78.100.204/handle/2XEOYT63/7960]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Meng, Zuqiang
作者单位1.Guangxi Univ, Coll Comp Elect & Informat, Nanning 530004, Peoples R China
2.Guangxi Univ, Guangxi Coll & Univ Key Lab Multimedia Commun & I, Nanning 530004, Peoples R China
3.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Meng, Zuqiang,Gan, Qiuling,Shi, Zhongzhi. On efficient methods of computing attribute-value blocks in incomplete decision systems[J]. KNOWLEDGE-BASED SYSTEMS,2016,113:171-185.
APA Meng, Zuqiang,Gan, Qiuling,&Shi, Zhongzhi.(2016).On efficient methods of computing attribute-value blocks in incomplete decision systems.KNOWLEDGE-BASED SYSTEMS,113,171-185.
MLA Meng, Zuqiang,et al."On efficient methods of computing attribute-value blocks in incomplete decision systems".KNOWLEDGE-BASED SYSTEMS 113(2016):171-185.

入库方式： OAI收割

来源：计算技术研究所

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