摘要
知识图谱以图结构表示丰富灵活的语义,描述客观世界的事物及其关系,在应用领域得到了广泛的关注。事件知识图谱聚焦动态事件及其间的顺承、时序和因果关系,并以结构化的图形式表示,对海量数据更高效地管理。尤其是对动态事件信息和事件逻辑关系的挖掘,对认识客观世界发展规律,助力领域多种智能应用有着重要的意义。本文系统阐述事件知识图谱的构建技术,包括事件知识表示、事件知识抽取、事件关系抽取,并介绍事件知识图谱在领域的典型应用,最后介绍现阶段的挑战与研究展望。
Given its rich and flexible semantics by the graph structure,knowledge graph which describes the things in the objective world and their relationships has received extensive attentions in many fields. In objective world,event knowledge graph focuses on various dynamic events,entities and their relationships in terms of structured graph for more efficient management of massive data. In particular,the mining of dynamic event information and event logic in the application field are of great significance for understanding the laws of world development and assisting various intelligent applications. The construction techniques and typical applications of event knowledge graph are reviewed in this article,including event knowledge representation,event knowledge extraction,and event relation extraction. The challenges and research perspectives are also discussed.
作者
项威
XIANG Wei(School of Electronic Information and Communications,Huazhong University of Science and Technology,Wuhan 430074,China)
出处
《计算机与现代化》
2020年第1期10-16,共7页
Computer and Modernization
基金
国家自然科学基金资助项目(61771209)
关键词
事件
知识图谱
构建技术
人工智能
深度学习
event
knowledge graph
construction technology
artificial intelligence
deep learning
