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Knowledge acquisition based on rough set and data mining
Guo HF(郭海峰); Zhou XM(周小明); Zhu YL(朱云龙)
作者部门先进制造技术实验室
会议名称2009 International Conference on Future BioMedical Information Engineering, FBIE 2009
会议日期December 13-14, 2009
会议地点Sanya, China
会议主办者International Science and Engineering Center; Intell. Inf. Technol. Appl. Res. Assoc.
会议录名称FBIE 2009 - 2009 International Conference on Future BioMedical Information Engineering
出版者IEEE Computer Society
出版地Piscataway, NJ, USA
2009
页码126-128
收录类别EI ; CPCI(ISTP)
EI收录号20101112764596
WOS记录号WOS:000290244100031
产权排序2
ISBN号978-1-4244-4691-9
关键词Cbr Case Knowledge Acquisition Rough Set Data Mining
摘要The case-based reasoning (CBR) becomes a novel paradigm that solves a new problem by remembering a previous similar situation and by reusing information and knowledge of that situation. However, the acquisition of case knowledge is a bottleneck within case-based reasoning. The use of rough set and data mining to discover knowledge from traditional database and to construct case base is desired. In this paper we discuss, in detail, the approach taken to acquire case knowledge. Rough set is used to preprocess the raw data that is noisy and redundant on the attribute. A Kohonen network is proposed to identify initial clusters within the data having been preprocessed. These clusters are then analyzed using C.45 and non-unique clusters are grouped to form concepts. Cases are then chosen from each of the identified concepts as well as outliers in the database. The results indicate that the proposed approach achieves a high reduction in the size of the case base.
语种英语
引用统计
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/19940
专题工业信息学研究室_先进制造技术研究室
通讯作者Guo HF(郭海峰)
作者单位1.College of Information Science and Engineering, Shenyang Ligong University, Shenyang, China
2.Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, China
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GB/T 7714
Guo HF,Zhou XM,Zhu YL. Knowledge acquisition based on rough set and data mining[C]//International Science and Engineering Center; Intell. Inf. Technol. Appl. Res. Assoc.. Piscataway, NJ, USA:IEEE Computer Society,2009:126-128.
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