Social Recommendation Algorithm Incorporating Graph Neural Network
FANG Deqiang
LI Ting
ZHANG Heng
Abstract：Traditional recommendation systems often ignore the differences between individuals on users,especially in social recommendation,where individuals have diverse influences on users on different items,leading to the decline of system perfor-mance and the unreliability of recommendation results.In order to overcome this problem,this paper proposes a recommendation al-gorithm based on attention mechanism.Firstly,the graph neural network is used to obtain the input information of users and items,and then the attention mechanism is introduced to effectively fuse users'personalized preferences.In addition,the introduction of multi-head attention mechanism helps to more comprehensively capture the complex dependency between users and users or items.Simulation results show that compared with traditional recommendation algorithms,this algorithm performs better in recommenda-tion performance,especially in more complex application scenarios.
Keywords：attention mechanismgraph neural networksdeep learning
Publication Date：2025-06-20
Online Publishing Date：2025-09-23(First online date of this platform, not the publication date of the document)
Pages：5( 40-43,54 )