Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (6A): 521-525.doi: 10.11896/JsJkx.190900131

• Database & Big Data & Data Science • Previous Articles     Next Articles

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).

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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

CLC Number: 

  • TP311
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