Abstract: The recommendation based on knowledge graph can improve the accuracy, diversity and interpretability of the recommendation. In this paper, a recommendation medel (LSKGCN) based on the convolution network of knowledge graphs and users’  long- and short-term preference is proposed. Based on the recommendation algorithm of knowledge graph, a user representation method combining long-term preference with short-term preference is proposed. According to the time, the recent history items are screened and the vector representation of the historical items is obtained by the convolution network algorithm of the knowledge graph, and the short-term interest expression is obtained by the attention mechanism. The long-term expression of interest is based on the minimum Euclidean distance from all historical items. Finally, real data sets Movielens-20, Amazon Music, Last.FM are used to test the validity of the algorithm.

Key words: knowledge graph, recommendation system, long- and short-term preference, graph convolutional network