Research on Artificial Intelligence Statistical Method for Session Recommendation Based on Fusion Improved GNN
In order to improve the recommendation accuracy of the session recommendation model,this study improved the graph neural network by constructing an in and out matrix,and designed an intelligent session recommendation model based on this.The test results are as follows:In all datasets,the model P@20 designed in this design is different from MRR@20 The values are 71.4 and 19.1 respectively,which are higher than the comparison model,and its standard deviation between P@20 and the average re-ciprocal ranking@20 under different session subsequences is 0.26 and 0.35,respectively.Test data shows that the session intelli-gent recommendation model designed this time has higher recommendation accuracy than traditional methods,and has certain applica-tion potential in intelligent customer service and intelligent interaction systems.
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