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    ARTICLE

    Combining Deep Learning with Knowledge Graph for Design Knowledge Acquisition in Conceptual Product Design

    Yuexin Huang1,2, Suihuai Yu1, Jianjie Chu1,*, Zhaojing Su1,3, Yangfan Cong1, Hanyu Wang1, Hao Fan4

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 167-200, 2024, DOI:10.32604/cmes.2023.028268 - 22 September 2023

    Abstract The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design. This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph. Specifically, the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data, and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design. Moreover, the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module, and uses multi-granularity information to overcome More >

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