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Relation-Wise Automatic Domain-Range Information Management for Knowledge Entries

机译:关于知识条目的关系 - Wise自动域系列信息管理

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Relations play a vital role on knowledge construction and maintenance thereof. They for example connect domain type entities to range type entities, like the relation born in connects some Persons to some Places. Over any dataset, the domain-range information is used to maintain data consistency. Therefore, we see that knowledge construction frameworks sometime engage costly Knowledge Engineers to define the domain-range information in form of a schema or an ontology. We also see that frameworks that hold such defined domain-range information, often do not follow them strictly. In the worst case some frameworks do not even allow to define a domain-range, rather they just gather the knowledge entries. One reason of not defining the domain-range information is that it is costly. On the other hand, the reason for not following the domain-range constraint is that the most of them are either manual or semi-automatic, therefore they face adaptation difficulty. In this research, we propose a relation-wise machine learning model that can define and validate domain-range information automatically. The initial experiment shows that the proposed framework performs promisingly.
机译:关系对知识建设和维护作出至关重要的作用。它们例如将域类型实体连接到范围类型实体,如将与某些人联系到某些地方的关系。在任何数据集上,域范围信息用于维护数据一致性。因此,我们看到知识施工框架有时聘用了昂贵的知识工程师,以架构或本体形式定义域范围信息。我们还看到持有这样定义的域范围信息的框架,通常不会严格遵循它们。在最坏的情况下,一些框架甚至没有允许定义域范围,而是收集知识条目。没有定义域范围信息的一个原因是它昂贵。另一方面,没有遵循域范围约束的原因是它们中的大多数是手动或半自动,因此它们面临适应难度。在这项研究中,我们提出了一个关系 - 明智的机器学习模型,可以自动定义和验证域范围信息。初步实验表明,所提出的框架承诺。

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