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

Author:

Huang Yongwen1,Jiang Zuhua1,He Chengneng2,Song Bo1,Liu Lijun1

Affiliation:

1. Department of Industrial Engineering, Shanghai Jiao Tong University, Shanghai, People’s Republic of China

2. Institute of Product Design, Shanghai Waigaoqiao Shipbuilding Company, Shanghai, People’s Republic of China

Abstract

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.

Publisher

SAGE Publications

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3