Session recommendation based on anonymous users ignores the possible cooperation information between different ses-sions and does not consider the correlation between the predicted target items and historical behavior,a session recommendation based on local-neighborhood graph information and attention mechanism(SR-LNG-AM)was proposed.The two types of project transformation information were learned from the graph structure constructed using the current session and neighborhood ses-sion,and they were fused to obtain the project embedding.The soft attention mechanism was used to generate the global embed-ding,and the target aware attention mechanism was used to adaptively generate different target embeddings for different target items.The local embedding was fused for prediction.Experiments were carried out on two real datasets.Compared with multi-ple baseline methods on two real datasets,the experimental indicators are all improved,which verifies the effectiveness of this method.
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