| 赵项,李正慧,吴正仲,陈永康.基于文献计量学的感性工学研究进展可视化分析[J].包装工程,2023,44(16):168-179. |
| 基于文献计量学的感性工学研究进展可视化分析 |
| Visual Analysis of Research Progress in Kansei Engineering Based on Bibliometrics |
| 投稿时间：2023-03-04 |
| DOI：10.19554/j.cnki.1001-3563.2023.16.017 |
| 中文关键词: 感性工学 知识图谱 可视化分析 文献计量 VOSviewer CiteSpace |
| 英文关键词: Kansei Engineering knowledge graph visual analysis bibliometrics VOSviewer CiteSpace |
| 基金项目:云南省保山高校社科联青年项目(BGQN2214);福建省引进台湾高层次人才“百人计划”专项基金项目(GY-S21081) |
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| 中文摘要: |
| 目的 为系统概括感性工学相关研究全局特征，进一步掌握当前感性工学研究进展，对相关文献研究热点、前沿趋势与理论基础等进行可视化分析。方法 以Web of Science核心合集数据库收录的感性工学相关文献数据作为样本，综合运用VOSviewer及CiteSpace软件对文献产出分布、作者、国家、合作机构、 |
| 英文摘要: |
| The work aims to carry out visual analysis on research hotspots in relevant literature, cutting-edge trends and theoretical foundations to systematically summarize the global characteristics of related research in Kansei Engineering, and further master the current research progress of Kansei Engineering. The literature data related to Kansei Engineering collected in the core database of Web of Science were used as the analysis sample, and VOSviewer and CiteSpace software were comprehensively adopted to draw the knowledge graph about the literature output distribution, author, country, partner institution, key word clustering and literature co-citation. Then, the research context of Kansei Engineering was sorted out through visual analysis. The number of related literature in Kansei Engineering is on the rise as a whole. China, Japan, Malaysia and other Asian countries are in the leading position in research, and the cooperation between regions and countries is close, but the cooperation between inter-regional institutions is relatively scattered. The research disciplines of Kansei Engineering are widely distributed, involving design, computer science, information science and other disciplines and showing a trend of multi-disciplinary cross-integration. The research hotspots mainly focus on product form design, process and method, perceptual evaluation, design knowledge and intelligent learning. The current research status is relatively mature, and a theoretical system based on Kansei Engineering design process and paradigm, semantic difference method and Kansei Engineering system has been formed. In addition, intelligent computing, big data, and text mining have become new trends in future research. |
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