文章摘要
倪敏娜,刘慧敏,薛景梵,张峰,易琦.基于大数据挖掘的宠物猫航空箱用户需求分析和设计研究[J].包装工程,2025,46(2):122-135.
基于大数据挖掘的宠物猫航空箱用户需求分析和设计研究
User Demand Analysis and Product Design of Pet Cat Air Carrier Based on Big Data Mining
投稿时间:2024-08-22  
DOI:10.19554/j.cnki.1001-3563.2025.02.011
中文关键词: 大数据挖掘  宠物猫航空箱  用户需求  产品设计
英文关键词: big data mining  pet cat air carrier  user demand  product design
基金项目:
作者单位
倪敏娜 东华大学上海 201620 
刘慧敏 东华大学上海 201620 
薛景梵 东华大学上海 201620 
张峰 上海诚唐文旅科技集团股份有限公司上海 200333 
易琦 东华大学上海 201620 
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中文摘要:
      目的 大数据中挖掘更加全面的用户需求,以优化宠物猫航空箱产品设计。方法 提出了一种基于大数据挖掘来获取宠物猫航空箱用户需求并对其展开分析的研究方法。首先对UGC平台评论进行语义提取及处理;其次构建需求要素模型,分析用户需求特征关系并可视化呈现;再次通过用户信息数据挖掘和定性调研绘制用户画像;最后整合用户需求特征与用户画像以构建用户行为地图,总结用户总体需求,并转化为设计需求,指导进一步设计实践和案例验证。结果 将设计需求映射为功能和解决方案,进行产品设计与开发,结合用户满意度检测验证其可行性。结论 对设计实践进行体验评价,结果表明结合大数据挖掘和用户需求定性分析的方法,能够有效、全面获取宠物猫航空箱的用户需求,为后续产品设计优化研究提供科学依据。
英文摘要:
      The work aims to mine more comprehensive user demands from big data to optimize the design of pet cat air carrier products. A research method was proposed based on big data mining to obtain the user demand of pet cat air carriers and analyze it. Firstly, the UGC platform comments were semantically extracted and processed; Secondly, a demand element model was constructed to analyze the relationship between user demand features and visually present them; After that, the user portraits were drawn through user information data mining and qualitative research; Finally, the user demand features and user portraits were integrated to construct a user behavior map, summarize the overall user demand, and transform it into design demands to guide further design practice and case validation. The design demands were mapped to functions and solutions. And on this basis, the design and development of pet cat air carriers were carried out. Afterwards, the feasibility was verified in conjunction with user satisfaction testing. In conclusion, the experience evaluation of design practice shows that the combination of the big data mining and qualitative analysis of user demands can effectively and comprehensively obtain user demands. It provides a scientific basis for subsequent design optimization research.
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