论文标题
EMAKG：Microsoft学术知识图的增强版本
EMAKG: An Enhanced Version Of The Microsoft Academic Knowledge Graph
论文作者
论文摘要
学术知识图是几个研究领域的宝贵信息来源。尽管与出版物和研究人员有关的现有数据集数量，但资源质量，覆盖范围和可访问性仍然有限。本文介绍了增强的Microsoft学术知识图，有关科学出版物和相关实体的大量信息以及开发的方法。数据包括地理信息，研究人员的协作网络以及机构之间的运动，学术相关指标和语言特征。数据集从多个数据源中合并信息，并具有高时空和空间7的覆盖范围，从而允许多种用例。
Scholarly knowledge graphs are valuable sources of information in several research fields. Despite the number of existing datasets related to publications and researchers, resource quality, coverage and accessibility are still limited. This article presents the Enhanced Microsoft Academic Knowledge Graph, a large dataset of information about scientific publications and involved entities, and the methods developed to build it. Data includes geographical information, researchers' collaborative networks and movements between institutions, academic-related metrics, and linguistic features. The dataset merges information from several data sources and has high temporal and spatial 7 coverage, allowing several use cases.
