Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 382-393 |
| Number of pages | 12 |
| Volume | 5914 LNAI |
| DOIs | |
| Publication status | Published - 2009 |
| Event | 3rd International Conference on Knowledge Science, Engineering and Management, KSEM 2009 - Vienna, Austria Duration: 2009 Nov 25 → 2009 Nov 27 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 5914 LNAI |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 3rd International Conference on Knowledge Science, Engineering and Management, KSEM 2009 |
|---|---|
| Country | Austria |
| City | Vienna |
| Period | 09/11/25 → 09/11/27 |
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Keywords
- Domain ontology
- Rule ontology
- Rule-based system
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
How much well does organizational knowledge transfer work with domain and rule ontologies? / Kobayashi, Keido; Yoshioka, Akiko; Okabe, Masao; Yanagisawa, Masahiko; Yamazaki, Hiroshi; Yamaguchi, Takahira.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5914 LNAI 2009. p. 382-393 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5914 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - How much well does organizational knowledge transfer work with domain and rule ontologies?
AU - Kobayashi, Keido
AU - Yoshioka, Akiko
AU - Okabe, Masao
AU - Yanagisawa, Masahiko
AU - Yamazaki, Hiroshi
AU - Yamaguchi, Takahira
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - Domain ontology
KW - Rule ontology
KW - Rule-based system
UR - http://www.scopus.com/inward/record.url?scp=77249153193&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77249153193&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-10488-6_37
DO - 10.1007/978-3-642-10488-6_37
M3 - Conference contribution
AN - SCOPUS:77249153193
SN - 3642104878
SN - 9783642104879
VL - 5914 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 382
EP - 393
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -