关键词: 推荐系统, 会话序列, 图数据库, 全局有向图, 全局偏好传播

Abstract: Aiming at the problem that the traditional recommendation algorithm in commodity session sequence recommendation relied too much on adjacent clicks and lost the overall commodity access trend to a certain extent, we proposed a new commodity session sequence recommendation algorithm based on global directed graph. Firstly, the global directed graph of commodity conversation sequence was constructed. The nodes in the graph were commodities, the arcs between nodes represented the click order, and the directed graph was stored in the graph database. Secondly, the global preference propagation strategy on the directed graph was given, and the important influence of click time on recommendation was considered. Finally, the score of the commodity to be recommended was obtained. On Diginetica and Yoochoose standard data sets, the recommended accuracy of the algorithm was improved by 6.12% and 30.25% respectively compared with the traditional Item-KNN method according to the P@20 standard, according to the MRR@20 standard, the recommended accuracy was improved by 15.04% and 33.88% respectively. The experimental results show that the proposed global directed graph search and scoring strategy is effective.

Key words:  recommendation system, session sequence, graph database, global directed digraph, global preference propagation