… of recommendation systems based on the knowledge graph. [… of recommendation algorithms based on knowledge graphs. Then, we sorted the development history of recommendation …
… neighbors. Based … graphconvolutionrecommendation model which combine neighbor importance sampling and feature cross pooling. The sampling method based on …
… the cold start problem of traditional recommendation models. But when extracting structured … of public neighbors; Secondly, it uses graphconvolutional neural networks to integrate the …
郭晓旺, 夏鸿斌, 刘渊 - … of Frontiers of Computer Science & …, 2022 - search.ebscohost.com
… recommendation model that combines knowledge graph and … Firstly, the KGCN (knowledge graphconvolutionalnetworks … vector of the item through neighborhood aggregation unit. The …
… interactive information and the multiple feature. A heterogeneous graphconvolutional neural network was … a recommendation link with strong interpretability, which greatly improved the …