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Knowledge recommender system for complex product development using ontology and vector space model

机译:使用本体和向量空间模型进行复杂产品开发的知识推荐系统

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摘要

Knowledge recommendation has become a trend to improve the efficiency of acquiring knowledge during product development. As such, coping with the challenge of constantly discovering new knowledge is critical for knowledge reuse. This article proposes a knowledge recommendation framework based on design tasks, to facilitate the capturing and sharing of knowledge in manufacturing firms. An ontology-based knowledge representation model is designed and developed to organize the knowledge resources and a vector space model-based knowledge recommendation model is built to hasten the knowledge reuse process. A case study demonstrates the effectiveness of the proposed method.
机译:知识推荐已成为提高产品开发过程中获取知识效率的趋势。因此,应对不断发现新知识的挑战对于知识重用至关重要。本文提出了一个基于设计任务的知识推荐框架,以促进制造企业中知识的获取和共享。设计并开发了一个基于本体的知识表示模型来组织知识资源,并建立了一个基于向量空间模型的知识推荐模型以加速知识的重用过程。案例研究证明了该方法的有效性。

著录项

  • 来源
    《Concurrent engineering》 |2019年第4期|347-360|共14页
  • 作者单位

    Guangxi Univ Sch Mech Engn Nanning 530004 Peoples R China|Natl Univ Singapore NUS Business Sch Singapore Singapore|Natl Univ Singapore Logist Inst Asia Pacific Singapore Singapore;

    CSIC Cross Technol Co Ltd Wuhan Hubei Peoples R China;

    Natl Univ Singapore NUS Business Sch Singapore Singapore|Natl Univ Singapore Logist Inst Asia Pacific Singapore Singapore;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    product development; knowledge recommender system; vector space model; ontology;

    机译:产品开发;知识推荐系统;向量空间模型本体论;

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