Extraction and linking of motivation, specification and structure of inventions for early design use

被引:5
|
作者
Jiang, Pingfei [1 ,4 ]
Atherton, Mark [2 ]
Sorce, Salvatore [3 ]
机构
[1] Kingston Univ London, Sch Engn & Environm, Dept Mech Engn, London, England
[2] Brunel Univ London, Coll Engn, Dept Mech & Aerosp Engn, London, England
[3] Koew Univ Enna, Faulty Engn & Architecture, Enna, Italy
[4] Kingston Univ London, Sch Engn & Environm, Dept Mech Engn, London SW15 3DW, England
关键词
Design representation; natural language processing; semantic network; design informatics; knowledge representation; WORD EMBEDDINGS; PATENT; GENERATION; VISUALIZATION; DATABASE; ART;
D O I
10.1080/09544828.2023.2227934
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Novel design creations often exist in the form of patents. It is well acknowledged that patents are a great source of design inspiration, therefore designers are encouraged to engage patents early in the design process. Studies of patent analysis have been carried out to benefit engineering design activities such as patent classification, technology forecasting, idea generation and emerging design-prior art comparison. However, the design intent behind inventions has received little attention in patent analysis. Designers can gain better design insight by looking at a patent from a systematic perspective starting from design intent to principal solutions. In this paper, an approach is proposed to extract and link the knowledge conveyed within patent descriptive sections to typical early engineering design stages, namely Motivation, Specification and Structure. This knowledge is then conceptualised into TRIZ engineering parameters and reconciled functional basis to enable cross-patent analysis. When compared to expert analysis, the proposed approach achieves an average of 63% accuracy with respect to Motivation, 56% with respect to Specification function and 44% with respect to Specification flow. Potential applications of such linking for early design use are then demonstrated through a prototype knowledge network.
引用
收藏
页码:411 / 436
页数:26
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