时态网络中知识图谱推荐:关键技术与研究进展

Recommendation Based on Knowledge Graph in Temporal Networks:Key Technologies and Progress

将知识图谱推荐系统应用于时态网络能够有效解决动态推荐问题,在军事、交通、社交等领域具有重要的应用价值。文中对时态网络中知识图谱推荐关键技术及进展进行综述,在总结了知识图谱基本概念、生命周期基础上,分析了知识图谱推荐系统的分类、构建流程及推荐算法特征,讨论了时态网络中知识图谱推荐关键技术,即知识推理和动态推荐的主要技术模型以及应用情况,并对该主题未来研究重点进行了展望分析,为相关领域研究提供借鉴和参考。

The application of knowledge graph-based recommendation systems in temporal networks can effectively solve the dynamic recommendation problem,which has important practical value in military,traffic,social and other related fields. This paper reviewed the key technologies and progresses of knowledge graph-based recommendation systems in temporal networks. First, classification, construction process and algorithm features of knowledge graph-based recommendation systems were analyzed. And then the main technical models and applications of knowledge reasoning and dynamic recommendation were addressed. At last,the future research focuses of this topic were proposed which may provide references for the related research.