How Much Well Does Organizational Knowledge Transfer Work with Domain and Rule Ontologies?

被引：0

作者：

Kobayashi, Keido ^{[1
]}

Yoshioka, Akiko ^{[1
]}

Okabe, Masao ^{[1
,2
]}

Yanagisawa, Masahiko ^{[2
]}

Yamazaki, Hiroshi ^{[2
]}

Yamaguchi, Takahira ^{[1
]}

机构：

[1] Keio Univ, Fac Sci & Technol, Dept Adm Engn, Kohoku Ku, 3-14-1 Hiyoshi, Yokohama, Kanagawa 2238522, Japan

[2] Tokyo Elect Power Co Ltd, Chiyoda ku, Tokyo 1008560, Japan

来源：

KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT | 2009年 / 5914卷

关键词：

domain ontology; rule ontology; rule-based system;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Knowledge transfer to next-generation engineers is an urgent issue in Japan. In this paper, we propose a new approach without costly OJT (on-the-job training), that is, combinational usage of domain and rule ontologies and a rule-based system. A domain ontology helps novices understand the exact meaning of the engineering rules and a rule ontology helps them get the total picture of the knowledge. A rule-based system helps domain experts externalize their tacit knowledge to ontologies and also helps novices internalize them. As a case study, we applied our proposal to some actual job. We also did an evaluation experiment for this case study and have confirmed that our proposal is effective.

引用

页码：382 / +

页数：3

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