计算机科学 ›› 2020, Vol. 47 ›› Issue (6A): 521-525.doi: 10.11896/JsJkx.190900131

• 数据库 & 大数据 & 数据科学 • 上一篇    下一篇

基于用户兴趣的农产品推荐技术研究

李建军, 付佳, 杨玉, 侯跃, 汪校铃, 荣欣   

  1. 哈尔滨商业大学计算机与信息工程学院 哈尔滨 150028 ;
    黑龙江省电子商务与信息处理重点实验室 哈尔滨 150028
  • 发布日期:2020-07-07
  • 通讯作者: 付佳(854616040@qq.com)
  • 作者简介:517718768@qq.com
  • 基金资助:
    国家自然科学基金项目(60975071);黑龙江省新型智库研究项目(18ZK015);黑龙江省哲学社会科学研究规划项目(17GLE298,16EDE16);哈尔滨商业大学校级课题(18XN065);哈尔滨商业大学博士科研启动基金(2019DS029)

Research on Agricultural Products Recommendation Technology Based on User Interest

LI Jian-Jun, FU Jia, YANG Yu, HOU Yue, WANG Xiao-ling and RONG Xin   

  1. School of Computer and Information Engineering,Harbin University of Commerce,Harbin 150028,China
    HeilongJiang Provincial Key Laboratory of Electronic Commerce and Information Processing,Harbin 150028,China
  • Published:2020-07-07
  • About author:LI Jian-Jun, associate professor, Ph.D.His main research interests include E-commerce and Business intelligence.
    FU Jia, born in 1996, graduate.Her main research interests include E-commerce and Business intelligence.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (60975071),HeilongJiang Province New Think Tank Research ProJect (18ZK015),HeilongJiang Province Philosophy and Social Science Research Planning ProJect (17GLE298,16EDE16),Harbin University of Commerce School-level ProJect (18XN065)and the Doctoral Research Foundation of Harbin University of Commerce (2019DS029).

摘要: 当前互联网发展日益强大,农产品电商市场的竞争愈演愈烈,用户无法从众多的产品信息中找到适合自身的产品,传统的协同过滤算法只关注用户评分,并不能及时反映用户的兴趣变化。针对这一问题,文中主要考虑通过用户行为及用户访问时间和频率,提出基于改进权值的用户兴趣推荐算法(Weight-based User Interest-Collaborative Filtering,WUI-CF)。实验结果表明,所提算法相比于传统推荐算法能更好地挖掘用户兴趣,适应用户的兴趣变化,提高推荐的精确度,能够更好地解决用户面临众多农产品信息无从挑选的问题,提高了用户的满意度。

关键词: 农产品, 频率权重, 时间权重, 推荐, 用户行为

Abstract: At present,the development of the Internet is becoming more and more powerful,and the competition in the e-commerce market of agricultural products is increasingly fierce.Users cannot find products suitable for themselves from a large amount of product information.The traditional collaborative filtering algorithm only pays attention to user ratings,and cannot reflect the changes of users’ interests in time.In view of this problem,a user interest recommendation algorithm based on improved weight was proposed by considering user behavior,user access time and frequency.Experimental results show that compared with the traditional recommendation algorithm,the proposed algorithm WUI-CF can better mine user interest,adapt to user’s interest changes,improve the accuracy of recommendation,and better solve the problem that users have no choice facing with numerous agricultural products information,and improve user satisfaction.

Key words: Agricultural products, Frequency weight, Recommendation, Time weight, User behavior

中图分类号: 

  • TP311
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