基于超图的智能产品服务系统知识表示模型

Wang Zuoxu, Li Xinyu, Chen Chun-hsien, Zheng Pai
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引用次数: 0

摘要

在数字化服务化的趋势下,制造企业通过将产品和相关服务捆绑在一起,将其业务模式转变为智能产品服务系统(Smart PSS)。为了支持智能PSS开发的知识密集型过程,需要对大量领域知识进行良好的组织和重用。然而,在智能PSS开发活动中,由于产品服务包(product-service bundles, PSB)和上下文感知问题所导致的非二元关系的存在,传统的基于图的知识表示方法在将非二元关系转换为二元关系的过程中可能会丢失重要信息,从而在后续的知识查询中导致错误的结果。为了解决这一问题,提出了一种基于超图的智能PSS知识表示模型,该模型表示具有超边的多个实体之间的非二元关系。在技术上,本文确定了智能PSS开发中的知识来源和典型的超边缘模式。通过对3D打印故障排除和PSB推荐场景的详细案例研究,展示了所提出的基于超图的知识表示模型,并验证了其有效性。结果表明,基于超图的知识模型通过添加多个超边,显著缓解了普通知识模型的稀疏性。期望所提出的超图知识表示模型可以作为进一步知识推理活动的基础研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hypergraph-Based Knowledge Representation Model for Smart Product-Service System Development
In the trend of digital servitization, manufacturing companies have been transforming their business paradigms to Smart product-service systems (Smart PSS) by integrating products and associated services as bundles. To support the knowledge-intensive process of Smart PSS development, massive domain knowledge should be well-organized and reused. However, due to the existence of non-binary relations caused by product-service bundles (PSB) and context-awareness concerns in the Smart PSS development activities, conventional graph-based approaches for knowledge representation may lose essential information in transforming non-binary relations into binary ones, and hence cause incorrect results in the subsequent knowledge queries. To mitigate this problem, a hypergraph-based knowledge representation model for Smart PSS was proposed, which represents the non-binary relations among multiple entities with hyperedges. Technically, the knowledge source and the typical hyperedge schema in Smart PSS development are identified in this paper. A detailed case study in the scenarios of 3D printing troubleshooting and PSB recommendation was conducted to showcase the proposed hypergraph-based knowledge representation model and demonstrate its validity. The results show that the hypergraph-based knowledge model significantly relieves the sparsity in the ordinary KG by adding multiple hyperedges. It is anticipated that the proposed hypergraph knowledge representation model can serve as a fundamental study for further knowledge reasoning activities.
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