Session recommendation method based on graph neural network
A technology of neural network and recommendation method, applied in the field of session recommendation based on graph neural network, which can solve the problems of simple session graph construction method, lack of session information, and inability to effectively use global session information, so as to improve recommendation effect and diversity , Reduce information loss, accuracy, scientific and effective effect
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[0044] like figure 1 Shown is a schematic flow chart of the method of the present invention: the graph neural network-based session recommendation method provided by the present invention includes the following steps:
[0045] S1. Construct a global conversation graph using all conversation sequences; the global conversation graph is constructed using all conversation sequence data. On the one hand, in order to reduce the complexity of the global conversation graph, too much noise is introduced, considering that users usually buy repeatedly or interact with some high-frequency commodities. Interaction, and at the same time, in order to capture the collaborative information between global session sequences; the specific implementation includes the following steps:
[0046] A. Traverse all session sequences and count the frequency of occurrence of all commodities;
[0047] B. According to the frequency of occurrence of all commodities counted in step A, select the high-frequenc...
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