Human Biographical Record (HBR)

Arash Nekoei, Fabian Sinn
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引用次数: 1

Abstract

We construct a new dataset of more than seven million notable individuals across recorded human history, the Human Biographical Record (HBR). With Wikidata as the backbone, HBR adds further information from various digital sources, including Wikipedia in all 292 languages. Machine learning and text analysis combine the sources and extract information on date and place of birth and death, gender, occupation, education, and family background. This paper discusses HBR's construction and its completeness, coverage, accuracy, and also its strength and weakness relative to prior datasets. HBR is the first part of a larger project, the human record project that we briefly introduce.
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人类传记记录(HBR)
我们构建了一个新的数据集,包含了人类历史上超过700万的著名人物,即人类传记记录(HBR)。以维基数据为基础,《哈佛商业评论》从各种数字资源中添加了更多的信息,包括所有292种语言的维基百科。机器学习和文本分析结合来源并提取有关出生和死亡日期和地点、性别、职业、教育程度和家庭背景的信息。本文讨论了HBR的结构及其完整性、覆盖面、准确性,以及相对于先前数据集的优缺点。HBR是一个更大项目的第一部分,我们简要介绍一下人类记录项目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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