现代纺织技术 ›› 2022, Vol. 30 ›› Issue (3): 210-215.DOI: 10.19398/j.att.202104026

• 服装工程 • 上一篇    下一篇

面向网购的服装尺码推荐系统构建与应用——以女式T恤为例

牛蒙蒙1, 吴长姣2, 卢业虎1,3, 汪明星4   

  1. 1.苏州大学纺织与服装工程学院,江苏苏州 215021;
    2.东南大学计算机科学与工程学院,南京 226300;
    3.南通纺织丝绸产业技术研究院,江苏南通 226311;
    4.南通紫罗兰家纺科技股份有限公司,江苏南通 226311
  • 收稿日期:2021-04-13 修回日期:2021-08-03 出版日期:2022-05-10 网络出版日期:2022-05-26
  • 通讯作者:卢业虎,E-mail: yhlu@suda.edu.cn
  • 作者简介:牛蒙蒙(1999-),女,河南周口人,硕士研究生,主要从事防护服装方面的研究。
  • 基金资助:
    南通市科技计划项目(JC2021004)

Establishment and application of online shopping garment size recommendation system: take women's t-shirts for example

NIU Mengmeng1, WU Changjiao2, LU Yehu1,3, WANG Mingxing4   

  1. 1. College of Textile and Clothing Engineering, Soochow University, Suzhou 215021, China;
    2. School of Computer Science and Engineering, Southeast University, Nanjing 211189, China;
    3. Nantong Textile and silk Industrial Technology Research Institute, Nantong 226300, China;
    4. Nantong Violet Home Textile Technology Co., Ltd., Nantong 226311, China
  • Received:2021-04-13 Revised:2021-08-03 Published:2022-05-10 Online:2022-05-26

摘要: 为了解决在服装网购过程中消费者不能现场试衣,导致所购服装合体性不佳、退货率较高的问题,以女式T恤为例,通过文献搜集、专家访谈和实证研究的方式,确立了服装关键部位的合体性松量阈值及不同廓形的判定标准,并以此为基础构建了一套完善的尺码推荐系统。系统数据库储存服装规格尺寸、用户个人尺寸等信息,前端采用bootstrap框架设计,后端使用C#语言开发,系统采用二次函数作为核心算法,通过计算与比较不同尺码的函数值,实现服装尺码智能推荐。经实验验证本系统的推荐准确率达88%以上,可以在一定程度上消除购物疑虑,减少物流成本,促进服装电子商务的发展。

关键词: 网购, 尺码推荐, 松量阈值, 服装廓形, 合体性

Abstract: In view that consumers cannot try on clothing purchased online, resulting in poor fitness and high refund of clothing, with women's T-shirts as an example, through literature collection, expert interviews and empirical research, the clothing fitness ease threshold of the key parts of clothing and the judging criteria for different silhouettes were determined, and a complete size recommendation system was established on this basis, which stores information such as clothing specifications and dimensions, user' personal information in the system database. The system front end was designed using bootstrap framework and the back end was developed using C# language. Adopting quadratic function as the core algorithm, the system is feasible to realize intelligent recommendation of clothing size by calculating and comparing the function values of different sizes. Through experimental verification, it is proved that the accuracy rate of this recommendation system can exceed 88%. It is conductive to eliminating consumers' shopping doubts to some extent, lowering logistics costs, and promoting the development of apparel e-commerce.

Key words: online shopping, size recommendation, clothing ease threshold, garment silhouette, fitness

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