Recommender system based on adaptive threshold filtering GCN

Meng Qiao, Hairen Gui, Ke Tang
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Abstract

We introduce the AT-GCN (Adaptive Threshold filtering Graph Convolutional Neural network model). AT-GCN is a recommendation model based on graph structure. Compared with the commonly used graph structure recommendation model, AT-GCN can effectively solve the problem of edge representation and information transfer, and improve the recommendation effect. In the experimental part, several groups of experiments were carried out on AT-GCN, and the above conclusions were finally verified by the experimental results.
基于自适应阈值滤波的GCN推荐系统
介绍了自适应阈值滤波图卷积神经网络模型(AT-GCN)。AT-GCN是一种基于图结构的推荐模型。与常用的图结构推荐模型相比,AT-GCN能有效地解决边缘表示和信息传递问题,提高推荐效果。实验部分在AT-GCN上进行了几组实验,最后通过实验结果验证了上述结论。
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