Repairing broken RDF links in the web of data

Mohammad Pourzaferani, M. Nematbakhsh
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引用次数: 7

Abstract

In the web of data, linked datasets are changed over time. These changes include updating on features and address of entities. The address change in RDF entities causes their corresponding links to be broken. Broken link is one of the major obstacles that the web of data is facing. Most approaches to solve this problem attempt to fix broken links at the destination point. These approaches have two major problems: a single point of failure; and reliance on the destination data source. In this paper, we introduce a method for fixing broken links which is based on the source point of links, and discover the new address of the detached entity. To this end, we introduce two datasets, which we call 'superior' and 'inferior'. Through these datasets, our method creates an exclusive graph structure for each entity that needs to be observed over time. This graph is used to identify and discover the new address of the detached entity. Afterward, the most similar entity, which is candidate for the detached entity, is deduced and suggested by the algorithm. The proposed model is evaluated with DBpedia dataset within the domain of 'person' entities. The result shows that most of the broken links, which had referred to a 'person' entity in DBpedia, had been fixed correctly.
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修复数据网络中损坏的RDF链接
在数据网络中,关联的数据集会随着时间而变化。这些变化包括对实体的功能和地址的更新。RDF实体中的地址更改会导致它们对应的链接中断。断链是数据网络面临的主要障碍之一。大多数解决此问题的方法都试图在目的点修复断开的链接。这些方法有两个主要问题:单点故障;以及对目标数据源的依赖。本文介绍了一种基于链接源点的修复断开链接的方法,并发现断开实体的新地址。为此,我们引入了两个数据集,我们称之为“优”和“劣”。通过这些数据集,我们的方法为每个需要随时间观察的实体创建一个独占的图结构。此图用于识别和发现分离实体的新地址。然后,通过算法推导和推荐最相似的实体作为分离实体的候选实体。提出的模型使用DBpedia数据集在“人”实体域中进行评估。结果显示,大多数在DBpedia中指向“person”实体的断裂链接已被正确修复。
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