Social Recommendation Model Based on Self-Supervised Graph Masked Neural Networks
ZANG Xiubo1, XIA Hongbin1,2, LIU Yuan1,2
1. School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122; 2. Jiangsu Key Laboratory of Media Design and Software Technology, Jiangnan University, Wuxi 214122
Abstract The existing self-supervised social recommendation models mostly construct self-supervised signals through the strategies of manual heuristic graph enhancement and contrasts between single-relational views. Thus, the performance of the model is easily affected by the quality of enhanced self-supervised signals, making it challenging to adaptively suppress noise. To solve these problems, a social recommendation model based on self-supervised graph masked neural networks(SGMN) is proposed. Firstly, single-relational views for user-social interaction and item classification are constructed respectively, as well as high-order connected heterogeneous graphs. Specifically, the graph masked learning paradigm is adopted to guide adaptive and learnable data augmentation for the user-social graph. Secondly, a heterogeneous graph encoder is designed to learn the latent semantics of the views, and cross-view contrastive learning is performed on user and item embeddings to complete self-supervised tasks. Then, weighted fusion is conducted on the user and item embeddings separately for recommendation task. Finally, a multi-task training strategy is employed to jointly optimize self-supervised learning, recommendation and graph masked tasks. Experiments on three real datasets demonstrate a certain performance improvement of SGMN.
Fund:National Natural Science Foundation of China(No.61972182)
Corresponding Authors:
XIA Hongbin, Ph.D., professor. His research interests include personalized recommendation and natural language processing.
About author:: ZANG Xiubo, master student. His research interests include recommendation system and deep learning.LIU Yuan, Ph.D., professor. His research interests include network security and social network.
ZANG Xiubo,XIA Hongbin,LIU Yuan. Social Recommendation Model Based on Self-Supervised Graph Masked Neural Networks[J]. Pattern Recognition and Artificial Intelligence, 2023, 36(10): 942-952.
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2023, Vol. 36 
