A Data Mining based Knowledge Management Approach for the Semiconductor Industry

被引:0
作者
Sassenberg, C. [1 ]
Weber, C. [1 ]
Fathi, M. [1 ]
Montino, R. [2 ]
机构
[1] Univ Siegen, Inst KBS & KM, Siegen, Germany
[2] ELMOS Semicond AG, ELMOS Cent IT Sev GmbH & Co KG, Dortmund, Germany
来源
2009 IEEE INTERNATIONAL CONFERENCE ON ELECTRO/INFORMATION TECHNOLOGY | 2009年
关键词
FEATURE-SELECTION;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
As organizations consider themselves to be exposed to intense global competition, knowledge has become more and more important. A successful Knowledge Management strategy is essential for organizations in the modern business world. For this task knowledge oftentimes should be gained out of data amounts, which are not human manageable. Therefore in conjunction with Knowledge Management Data Mining is used by many organizations to transform raw data into knowledge. Among the many fields of applications the semiconductor industry is an example. In order to ensure an effective and significant analysis of the production process, a huge amount of data has to be gathered and interpreted. In this paper we present a framework processing these data. We will demonstrate how Data Mining methods could be used to support the process of finding solutions to technical problems by applying Knowledge Management.
引用
收藏
页码:70 / +
页数:3
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