An inner-enterprise wiki system integrated with semantic search for reuse of lesson-learned knowledge in product design

In the process of product design, it is usually difficult for engineers to find and reuse others’ lesson-learned knowledge, which is usually not well collected by an enterprise. This study proposes a model of an inner-enterprise wiki system integrated with a semantic search framework to support the...

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Veröffentlicht in:Proceedings of the Institution of Mechanical Engineers. Part B, Journal of engineering manufacture Journal of engineering manufacture, 2016-03, Vol.230 (3), p.548-561
Hauptverfasser: Huang, Yongwen, Jiang, Zuhua, He, Chengneng, Song, Bo, Liu, Lijun
Format: Artikel
Sprache:eng
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Zusammenfassung:In the process of product design, it is usually difficult for engineers to find and reuse others’ lesson-learned knowledge, which is usually not well collected by an enterprise. This study proposes a model of an inner-enterprise wiki system integrated with a semantic search framework to support the accumulation and reuse of lesson-learned knowledge in product design. The accumulated wiki web pages in inner-enterprise wiki system can be viewed as a large lesson-learned knowledge repository, which stores engineers’ wisdom of product design and is the basis of semantic search for knowledge reuse. The semantic-based knowledge search mechanism of inner-enterprise wiki system is presented, which can overcome limitations of traditional keyword-based search in existing wiki systems. To validate our approach, an inner-enterprise wiki system implementation is introduced and some experiments are done. Effectiveness of semantic search mechanism in inner-enterprise wiki system is verified from several viewpoints such as comparison of precision and recall between proposed method and a keyword-based one. The performance of utilizing inner-enterprise wiki system for knowledge reuse is evaluated and the results show that inner-enterprise wiki system can improve the performance of learning. The promising results confirm the feasibility of our approach in helping engineers to better reuse needed lesson-learned knowledge.
ISSN:0954-4054
2041-2975
DOI:10.1177/0954405414555739