竞赛
计算机科学
知识图
图形
领域知识
构造(python库)
知识抽取
人工智能
数据科学
理论计算机科学
程序设计语言
政治学
法学
作者
Xindong Wu,Jia Wu,Xiaoyi Fu,Jiachen Li,Peng Zhou,Xu Jiang
标识
DOI:10.1109/icdm.2019.00204
摘要
Automatic knowledge graph construction seeks to build a knowledge graph from unstructured text in a specific domain or cross multiple domains, without human intervention. IEEE ICDM 2019 and ICBK 2019 invited teams from both degree-granting institutions and industrial labs to compete in the 2019 Knowledge Graph Contest by automatically constructing knowledge graphs in at least two different domains. This article reports the outcomes of the Contest. The participants were expected to build a model to extract knowledge represented as triplets from text data and develop a web application to visualize the triplets. Awards were given to five teams. Their models and key techniques used to construct knowledge graphs are summarized.
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