计算机应用与软件2024，Vol.41Issue(8)：289-297,9.DOI:10.3969/j.issn.1000-386x.2024.08.042
基于图注意力对抗网络的社会化推荐系统
SOCIAL RECOMMENDATION SYSTEM BASED ON GRAPH ATTENTION ADVERSARIAL NETWORK
摘要
Abstract
Existing recommendation systems cannot distinguish social influence from potential interest well,and ignore the graph structure characteristics and changes of social networks.In view of the above deficiencies,a social recommendation system based on graph attention adversarial network(GAASR)is proposed.Social influence and potential interest were separated by adversarial network.Hadamard projection method was used to obtain the values of context weight.The graph attention network was used to learn the potential vector of social embedding and capture the social structure of users more accurately.In order to verify the performance of the recommendation system,three recommendation system data sets were used for analysis experiments.The experimental results show that GAASR is better than currently popular recommendation methods,which can effectively improve the recommendation accuracy.关键词
推荐系统/生成对抗网络/图注意力网络/社交网络Key words
Recommendation system/Generative adversarial network/Graph attention network/Social network分类
信息技术与安全科学引用本文复制引用
夏忠秀,张维玉,翁自强,郭新超..基于图注意力对抗网络的社会化推荐系统[J].计算机应用与软件,2024,41(8):289-297,9.基金项目
国家重点研发计划项目(2018YFC0831704) （2018YFC0831704）
国家自然科学基金项目(61502259) （61502259）
山东省自然科学基金项目(ZR2017MF056). （ZR2017MF056）
