The essence of knowledge (bases) through entity rankings

Evica Milchevski, S. Michel, A. Stupar
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引用次数: 10

Abstract

We consider the task of automatically phrasing and computing top-k rankings over the information contained in common knowledge bases (KBs), such as YAGO or DBPedia. We assemble the thematic focus and ranking criteria of rankings by inspecting the present Subject, Predicate, Object (SPO) triples. Making use of numerical attributes contained in the KB we are also able to compute the actual ranking content, i.e., entities and their performances. We further discuss the integration of existing rankings into the ranking generation process for increased coverage and ranking quality. We report on first results obtained using the YAGO knowledge base.
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知识(基础)的本质通过实体排名
我们考虑在公共知识库(KBs)(如YAGO或DBPedia)中包含的信息上自动措辞和计算top-k排名的任务。我们通过检查当前的主语、谓语、宾语(SPO)三元组来组合主题焦点和排名标准。利用知识库中包含的数字属性,我们还能够计算实际的排名内容,即实体及其性能。我们进一步讨论将现有排名集成到排名生成过程中,以增加覆盖率和排名质量。我们报告使用YAGO知识库获得的第一个结果。
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