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EventKG-一个以事件为中心的多语言时态知识图

EventKG- A Multilingual Event-Centric Temporal Knowledge Graph
课程网址: http://videolectures.net/eswc2018_gottschalk_knowledge_graph/  
主讲教师: Simon Gottschalk
开课单位: 内华达大学
开课时间: 2018-07-10
课程语种: 英语
中文简介:
促进对网络、新闻和社交媒体上的当代和历史事件信息进行语义分析的关键要求之一是提供包含事件和时间关系的综合表示的参考知识库。现有的知识图,包括DBpedia、YAGO和Wikidata等流行示例,主要集中于以实体为中心的信息,在事件和时间关系的覆盖范围和完整性方面不够。本文介绍的EventKG是一个以事件为中心的多语言时态知识图,旨在解决这一差距。EventKG包含了超过69万个当代和历史事件,以及从多个大型知识图和结构化程度较低的源中提取的超过230万个时间关系,并通过规范表示提供了这些信息。在本文中,我们介绍了EventKG,包括它的数据模型、提取过程和特征,并讨论了它与几个现实世界应用的相关性,包括问答、时间线生成和跨文化分析。
课程简介: One of the key requirements to facilitate semantic analytics of information regarding contemporary and historical events on the Web, in the news and in social media is the availability of reference knowledge repositories containing comprehensive representations of events and temporal relations. Existing knowledge graphs, with popular examples including DBpedia, YAGO and Wikidata, focus mostly on entity-centric information and are insufficient in terms of their coverage and completeness with respect to events and temporal relations. EventKG presented in this paper is a multilingual event-centric temporal knowledge graph that aims to address this gap. EventKG incorporates over 690 thousand contemporary and historical events and over 2.3 million temporal relations extracted from several large-scale knowledge graphs and less structured sources and makes this information available through a canonical representation.In this paper we present EventKG including its data model, extraction process, and characteristics and discuss its relevance for several real-world applications including Question Answering, timeline generation and cross-cultural analytics.
关 键 词: 语义分析; 参考知识库; 数据模型
课程来源: 视频讲座网
数据采集: 2022-12-19:chenjy
最后编审: 2023-05-11:chenjy
阅读次数: 27