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计算机技术21年12期

服装推荐服务平台的研究与开发
郭玉芝,林朝阳
(青岛工学院,山东 青岛 266300)

摘  要:随着互联网技术的发展,越来越多的电商服务平台使用推荐算法来提高用户的购物体验,以此促进消费。该平台主要研究基于协同过滤推荐算法实现服装推荐功能,并实现店铺入驻、服装商品管理、商品交易、服装推荐、消息会话、圈子发现功能。平台采用前后端分离的开发方式,运用 Spring Boot+MySQL+MyBatis+Vue 等技术完成平台的设计与实现。


关键词:推荐算法;Spring Boot;服务平台;Vue



DOI:10.19850/j.cnki.2096-4706.2021.12.029


基金项目:山东省本科教学改革研究项目 (M2020157)


中图分类号:TP311                                       文献标识码:A                                      文章编号:2096-4706(2021)12-0107-03


Research and Development of Clothing Recommendation Service Platform

GUO Yuzhi, LIN Chaoyang

(Qingdao Institute of Technology, Qindao 266300, China)

Abstract: With the development of internet technology, more and more e-commerce service platforms use recommendation algorithms to improve the users' shopping experience, thereby promoting consumption. For the platform, we mainly study the realization of clothing recommendation function based on collaborative filtering recommendation algorithm, and realize the functions of store entry, clothing commodity management, commodity transaction, clothing recommendation, message conversation and circle discovery. Adopting the development mode of front and rear end separation, the platform is designed and implemented by using Spring Boot+MySQL+MyBatis+Vue and other technologies.

Keywords: recommendation algorithm; Spring Boot; service platform; Vue


参考文献:

[1] HE X N,LIAO L L,ZHANG H W,et al. Neural collaborative filtering [C]//WWW '17:Proceedings of the 26th International Conference on World Wide Web.Perth:International World Wide Web Conferences Steering Committee,2017:173-182.

[2] 陈军,谢卫红,陈扬森 . 国内外大数据推荐算法领域前沿 动态研究 [J]. 中国科技论坛,2018(1):173-181.

[3] 林伟婷 .C/S 与 B/S 架构技术比较分析 [J]. 科技资讯, 2018,16(13):15-16.

[4] LIU J,WANG D,DING Y. PHD:A Probabilistic Model of Hybrid Deep Collaborative Filtering for Recommender Systems [J]. Journal of Machine Learning Research,2017:224-239.

[5] 雷曼,龚琴,王纪超,等 . 基于标签权重的协同过滤推荐 算法 [J]. 计算机应用,2019,39(3):634-638.


作者简介:郭玉芝(1985.01—),女,汉族,山东即墨人, 副教授,硕士研究生,研究方向:软件质量管理、数据库应用。