面向用户的个性化产品服务系统协同过滤推介方法  

Method of collaborative filtering recommendation of personalized product-service system based on user

作　　者：吕锋[1,2] 李念 冯壮壮 张杨航 LYU Feng;LI Nian;FENG Zhuang-zhuang;ZHANG Yang-hang(School of Mechatronics Engineering,Henan University of Science and Technology,Luoyang 471003,China;Collaborative Innovation Center of Machinery,Equipment Advanced Manufacturing of Henan Province,Luoyang 471003,China;International School,Beijing University of Posts and Telecommunications,Beijing 100876,China)

机构地区：[1]河南科技大学机电工程学院,河南洛阳471003 [2]机械装备先进制造河南省协同创新中心,河南洛阳471003 [3]北京邮电大学国际学院,北京100876

出　　处：《吉林大学学报（工学版）》2023年第7期1935-1942,共8页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家重点研发计划项目(2020YFB1713500);河南省高等学校重点科研项目计划项目(20B410002).

摘　　要：为快速准确地为用户推介新产品服务系统,提出了改进的协同过滤推介模型。首先,确定目标用户邻居集,针对传统协同过滤算法中数据冷启动问题,提出了用户属性相似度和用户体验相似度相结合的方法,并引入Jaccard系数、平均评分修正系数、热门系数,提高用户体验相似度的准确性。其次,确定新产品服务系统相似集,针对传统基于项目的协同过滤算法忽略项目属性对相似性制约的问题,提出了基于产品服务系统属性的改进皮尔逊余弦相似度算法,应用BP神经网络获得不同产品服务系统下各属性的客观权重,提高了属性重要度的可靠性。最后,构建了新产品服务系统的推介准则。以拖拉机产品服务系统推介为例,验证了所提模型的可行性和有效性。An improved collaborative filtering recommendation model is proposed to recommend the new product service system for users quickly and accurately.Firstly,the target user neighbor set is determined.Aiming at the problem of data cold start in the traditional collaborative filtering algorithm,a method combining user attribute similarity and user experience similarity is proposed,and Jaccard coefficient,average score correction coefficient and popular coefficient are introduced to improve the accuracy of user experience similarity.Then,the similarity set of new product service system is determined.An improved Pearson cosine similarity algorithm based on product service system attributes is proposed to solve the problem that the traditional project-based collaborative filtering algorithm ignores the similarity constraints of project attributes,and BP neural network is used to obtain the objective weight of each attribute under different product service systems,which improves the reliability of attribute importance.Finally,the recommendation guideline to judge whether the new product service system can be recommended to target user is constructed.Taking the tractor service system recommendation as an example,the feasibility and effectiveness of recommendation model are verified.

关 键 词：农业工程 产品服务系统 协同过滤 皮尔逊相似度 余弦相似度 BP神经网络 推介 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]