新一代知识图谱关键技术综述

近年来，国内外在新一代知识图谱的关键技术和理论方面取得了一定进展，以知识图谱为载体的典型应用也逐渐走进各个行业领域，包括智能问答、推荐系统、个人助手等.然而，在大数据环境和新基建背景下，数据对象和交互方式的日益丰富和变化，对新一代知识图谱在基础理论、体系架构、关键技术等方面提出新的需求，带来新的挑战.将综述国内外新一代知识图谱的关键技术研究发展现状，重点从非结构化多模态数据组织与理解、大规模动态图谱表示学习与预训练模型、神经符号结合的知识更新与推理3方面对国内外研究的最新进展进行归纳、比较和分析.最后，就未来的技术挑战和研究方向进行展望.

Survey on Key Technologies of New Generation Knowledge Graph

With the wave of the past decade, the development of artificial intelligence is in the critical period from perceptual intelligence to cognitive intelligence. Knowledge graph, as the core technique of knowledge engineering in the era of big data, is the combination of symbolism and connectionism, and is the cornerstone of realizing cognitive intelligence. It provides an effective solution for the knowledge organization and intelligent application in the Internet era. In recent years, some progress has been made in the key technologies and theories of knowledge graph, and typical applications of knowledge graph based on information system have gradually entered various industries, including intelligent question answering, recommendation system, personal assistant, etc. However, in the context of big data environment and new infrastructure of China, the increasing multi-modal data and new interaction ways have raised new demands and brought new challenges to the new generation of knowledge graph in terms of basic theory, architecture, and key technologies. We summarize the research and development status of key technologies of the new generation knowledge graph at home and abroad, including unstructured multi-modal data organization and understanding, large-scale dynamic knowledge graph representation learning and pre-training models, and neural-symbolic knowledge inference. We summarize, compare and analyze the latest research progress. Finally, the future technical challenges and research directions are prospected.