Knowledge acquisition based on rough set and data mining
文献类型：会议论文
| 作者 | Guo HF(郭海峰); Zhou XM(周小明); Zhu YL(朱云龙)
|
| 出版日期 | 2009 |
| 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 |
| 关键词 | CBR Case Knowledge Acquisition Rough Set Data Mining |
| 页码 | 126-128 |
| 通讯作者 | 郭海峰 |
| 中文摘要 | 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. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 2 |
| 会议主办者 | International Science and Engineering Center; Intell. Inf. Technol. Appl. Res. Assoc. |
| 会议录 | FBIE 2009 - 2009 International Conference on Future BioMedical Information Engineering
 |
| 会议录出版者 | IEEE Computer Society |
| 会议录出版地 | Piscataway, NJ, USA |
| 语种 | 英语 |
| ISBN号 | 978-1-4244-4691-9 |
| WOS记录号 | WOS:000290244100031 |
| 源URL | [http://ir.sia.cn/handle/173321/19940]  |
| 专题 | 沈阳自动化研究所_工业信息学研究室_先进制造技术研究室 |
| 推荐引用方式 GB/T 7714 | Guo HF,Zhou XM,Zhu YL. Knowledge acquisition based on rough set and data mining[C]. 见:2009 International Conference on Future BioMedical Information Engineering, FBIE 2009. Sanya, China. December 13-14, 2009. |
入库方式： OAI收割
来源：沈阳自动化研究所
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