Semantic Reasoning of Product Biologically Inspired Design Based on BERT
Semantic Reasoning of Product Biologically Inspired Design Based on BERT
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DOI：
10.3390/app112412082
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发表时间：
2021-12
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影响因子：
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通讯作者：
Ze Bian;Shijian Luo;Fei Zheng;Liuyu Wang;Ping Shan
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文献类型：
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作者：
Ze Bian;Shijian Luo;Fei Zheng;Liuyu Wang;Ping Shan
仿生推理是产品仿生设计中的一个重要过程，设计师在这个过程中寻找与设计相匹配的生物和产品。一些研究试图帮助设计师进行仿生推理，但仍然存在局限性。设计师在产品BID中的仿生推理思维是模糊的，缺乏句子层面的模糊语义搜索方法。本研究试图协助设计师在产品BID中进行仿生语义推理。首先，通过实验确定设计者在自上而下和自下而上两种过程中的仿生推理思维。获得了包括情感感知、形式、功能、材料和环境的仿生映射关系。其次，采用双向编码器表示转换器（BERT）预训练模型计算产品描述语句和生物语句的语义相似度，使设计者能够选择排序高的结果完成仿生推理。最后，以产品BID为例，展示了仿生语义推理过程，验证了该方法的可行性。
Bionic reasoning is a significant process in product biologically inspired design (BID), in which designers search for creatures and products that are matched for design. Several studies have tried to assist designers in bionic reasoning, but there are still limits. Designers’ bionic reasoning thinking in product BID is vague, and there is a lack of fuzzy semantic search methods at the sentence level. This study tries to assist designers’ bionic semantic reasoning in product BID. First, experiments were conducted to determine the designer’s bionic reasoning thinking in top-down and bottom-up processes. Bionic mapping relationships, including affective perception, form, function, material, and environment, were obtained. Second, the bidirectional encoder representations from transformers (BERT) pretraining model was used to calculate the semantic similarity of product description sentences and biological sentences so that designers could choose the high-ranked results to finish bionic reasoning. Finally, we used a product BID example to show the bionic semantic reasoning process and verify the feasibility of the method.