论文标题
dabeano：表与知识图实体注释
TabEAno: Table to Knowledge Graph Entity Annotation
论文作者
论文摘要
在开放数据时代，网络和数据门户上已提供大量的表资源。但是，由于实体，名称变化，异质模式，缺失或不完整的元数据的歧义，很难直接使用此类数据。为了解决这些问题，我们提出了一种新颖的方法，即dabeano，以语义注释桌子行向知识图实体。具体而言，我们引入了一个“两个细胞”查找策略基础，假设在表的同一行中的两个封闭的单元格之间的知识图中存在现有的逻辑关系。尽管方法很简单，但Dabeano的表现优于两个标准数据集中的艺术状态，例如，带有T2D，Limaye和大型Wikipedia表数据集中的T2D，Limaye。
In the Open Data era, a large number of table resources have been made available on the Web and data portals. However, it is difficult to directly utilize such data due to the ambiguity of entities, name variations, heterogeneous schema, missing, or incomplete metadata. To address these issues, we propose a novel approach, namely TabEAno, to semantically annotate table rows toward knowledge graph entities. Specifically, we introduce a "two-cells" lookup strategy bases on the assumption that there is an existing logical relation occurring in the knowledge graph between the two closed cells in the same row of the table. Despite the simplicity of the approach, TabEAno outperforms the state of the art approaches in the two standard datasets e.g, T2D, Limaye with, and in the large-scale Wikipedia tables dataset.
