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Research on Product Conceptual Design Methods and Ontology Construction Based on Knowledge Graphs
DOI: https://doi.org/10.62381/I245601
Author(s)
Yongzheng Tie1,*, Xian Zhou2, Ying Nie1
Affiliation(s)
1School of Mechatronic Engineering, Xi'an Technological University, Xi'an, Shaanxi, China 2School of Art and Media, Xi'an Technological University, Xi'an, Shaanxi, China *Corresponding Author.
Abstract
Product concept design is a complex process, the existing design methods in a short period of time to provide designers with very limited design ideas, with the aid of emerging technologies for product design will greatly improve the design efficiency, through the construction of knowledge graph will help designers in a short period of time to find the design ideas to improve the design efficiency. Through the study of knowledge graph, the knowledge graph construction process in the field of product design has been established. This paper takes automobile as an example, conducts data collection of design knowledge, and obtains a preliminary corpus of design knowledge through data processing. After data analysis, five major categories are identified for ontology construction. Based on the ontology knowledge, the ontology layer of automobile appearance design is constructed by utilizing the seven-step method, so as to do the prospective work for the knowledge graph construction in the design field.
Keywords
Knowledge Graph; Product Design; Design Methodology; Data Mining; Ontology Layer
References
[1] Zhu Degang, Guang Lin, Tang Sheng, et al. A conceptual design method for product innovation based on patent knowledge mapping. Computer Integrated Manufacturing Systems, 2022, 28 (11): 3599-3614. [2] Pu Zhang. Research on product conceptual design and evaluation based on digital twin. Huazhong University of Science and Technology,2022. [3] Chen Yue, Liu Zeyuan. Quietly emerging scientific knowledge mapping[j]. Research in Science, 2005, (02): 149-154. [4] Fu Leijie, Cao Yan, Bai Yu, et al. Development status and outlook of domestic vertical domain knowledge graph. Computer Application Research,2021,38(11):3201-3214. [5] Wang Meng, Wang Jingting, Jiang Yinlin, et al. Human-computer hybrid active search for knowledge graphs. Computer Research and Development 57.12(2020):2501-2513. [6] Christian Bizer, Jens Lehmann, Georgi Kobilarov, et al. Dbpedia-a crystallization point for the web of data. Journal of Web Semantics 7.3 (2009): 154-165. [7] Suchanek, Fabian M., Gjergji Kasneci, et al. Yago: A large ontology from wikipedia and wordnet. Journal of Web Semantics 6.3 (2008): 203-217. 203-217. [8] Huang Hengqi, Yu Juan, Liao Xiao, et al. A Review of Knowledge Graph Research Computer System Applications, 2019, 28 (06): 1-12. [9] Cheng Can, Zhao Jinghua. Sentiment Analysis of New Energy Vehicle User Comments Based on BERT and VADER Rules. Intelligent Computers and Applications, 1-12 [2022-09-05]. [10] Wang Peng, Xing Zhihong. A review on semantic mining of product design imagery based on big data. Design, 2023, 36 (16): 84-87.
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