To distinguish the importance of different review data for different users and items in the recommendation algorithm based on review,a recommendation algorithm combining attention mechanism and review feature was proposed(RAAM).A three-level attention mechanism was added into the convolutional neural network to distinguish the importance of comments for users or items from word level,sentence level and comment level.A co-attention network was introduced to simulate the interac-tion between the user and the item,so more fine-grained interaction characteristics were obtained.Experimental results on five Amazon data sets verify the effectiveness of the recommendation algorithm.
维普
万方数据