计算机科学与探索2024，Vol.18Issue(5)：1368-1382,15.DOI:10.3778/j.issn.1673-9418.2304025
结合用户共同意图及社交关系的群组推荐方法
Group Recommendation Model Based on User Common Intention and Social Interaction
摘要
Abstract
Existing group recommendation models often have a monotonous approach when solving user representa-tion,and only simple social relationships between users are utilized.This makes user representation inaccurate and most models do not consider the impact of user common intention and social interaction on group preferences.As a result,recommended items are not aligned with user needs.To address these issues,a new group recommendation model based on user common intention and social interaction(GR-UCISI)is proposed.Firstly,a user intention sepa-ration model that combines user-item interaction history with social interaction is constructed.Graph neural net-works are utilized to collect user-item interaction and social interaction information,and to solve user intention and item representation.Secondly,by utilizing the social network random walk algorithm and the K-means clustering algorithm,users can be grouped.User group,user intention and group intention aggregation process are combined to obtain group common intention representation.Finally,group common intention representation and item represen-tation are calculated to obtain the list of recommended items for the group.This method fully considers the impact of user individuality and commonality among group members on group preferences.It also utilizes social relation-ships to alleviate the problem of data sparsity and improve model performance.The experimental results show that compared with the model with the best recommendation effect of nine models,on the Gowalla dataset,the Precision and NDCG of the GR-UCISI model are increased by 3.01%and 5.26%respectively,on the Yelp-2018 dataset,the Precision and NDCG of the GR-UCISI model are increased by 2.96%and 1.12%respectively.关键词
群组推荐/用户共同意图/社交关系/图神经网络Key words
group recommendation/user common intention/social interaction/graph neural network分类
信息技术与安全科学引用本文复制引用
钱忠胜,张丁,李端明,王亚惠,姚昌森,俞情媛..结合用户共同意图及社交关系的群组推荐方法[J].计算机科学与探索,2024,18(5):1368-1382,15.基金项目
国家自然科学基金(62262025) （62262025）
江西省自然科学基金(20224ACB202012) （20224ACB202012）
江西财经大学第十八届学生科研课题(20231015153816912). This work was supported by the National Natural Science Foundation of China(62262025),the Natural Science Foundation of Jiangxi Province(20224ACB202012),and the 18th Student Research Project of Jiangxi University of Finance and Economics(20231015153816912). （20231015153816912）
