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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Developing an ontology-based knowledge combination mechanism to customise complementary knowledge content
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Developing an ontology-based knowledge combination mechanism to customise complementary knowledge content

机译：开发基于本体的知识组合机制以定制补充知识内容

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摘要

In rapidly changing business environments, enterprises are encountering increasingly complicated and multidimensional challenges related to R&D and manufacturing processes. To address these challenges, knowledge requesters working for these enterprises must effectively gain knowledge from enterprise knowledge bases, other enterprises or knowledge markets. However, knowledge requesters cannot obtain a desired and distinctive solution from a single knowledge source, including their own enterprise knowledge base. If knowledge can be customised by combining knowledge from various sources to create personalised complementary knowledge combinations that are more suited to their knowledge requirements, then knowledge acquisition and searches invariably become more efficient and accurate. Therefore, an ontology-based complementary knowledge combination mechanism, which can be employed to enhance online digitised knowledge recommendations or enterprise knowledge management systems, was developed in this study. First, a knowledge requirement model and a knowledge-product ontology model was constructed to describe and structure knowledge content, and then an ontology similarity calculation method was developed to enable precise comparisons of the requirements and knowledge structuralised by the knowledge requirement and product models. Finally, according to the four indicators of similarity, duplication, amount of knowledge and cost, a genetic algorithm (GA)-based knowledge-product ontology combination method was developed to identify optimal knowledge combinations and subsequently provide a reference for knowledge requesters.
机译：在瞬息万变的商业环境中，企业正面临与研发和制造流程相关的日益复杂和多维的挑战。为了应对这些挑战，为这些企业工作的知识请求者必须有效地从企业知识库，其他企业或知识市场中获取知识。但是，知识请求者无法从单个知识源（包括他们自己的企业知识库）中获得所需的独特解决方案。如果可以通过组合来自各种来源的知识来定制知识，以创建更适合其知识要求的个性化互补知识组合，那么知识获取和搜索将始终变得更加高效和准确。因此，本研究开发了一种基于本体的互补知识组合机制，可用于增强在线数字化知识推荐或企业知识管理系统。首先，构造知识需求模型和知识产品本体模型来描述和构造知识内容，然后开发一种本体相似度计算方法，以实现由知识需求和产品模型构成的需求和知识的精确比较。最后，根据相似性，重复性，知识量和成本这四个指标，开发了一种基于遗传算法的知识产品本体组合方法，用于识别最优知识组合，为知识请求者提供参考。

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