An improved recommendation model of knowledge graph attention
Because of the problem that the knowledge graph attention network(Knowledge Graph At-tention Network,KGAT)recommendation model spreads information on the whole knowledge graph and is easy to lose a large amount of feature information,an improved knowledge graph at-tention network model is proposed,which replaces the attention mechanism by a two-way atten-tion mechanism to improve the accuracy of recommendation.Finally,comparative experiments were conducted on two public datasets,Amazon-Book and Last-FM.The experimental results showed that the improved model was improved in the evaluation indexes of Recall and NDCG,by 1.81%and 1.68%,respectively,and 1.26%and 1.35%on Last-FM,respectively,effectively im-proving the recommendation effect.