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Repairing broken RDF links in the web of data

Repairing broken RDF links in the web of data 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Web Engineering and Technology Inderscience Publishers

Repairing broken RDF links in the web of data

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1476-1289
eISSN
1741-9212
DOI
10.1504/IJWET.2013.059106
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of Web Engineering and Technology – Inderscience Publishers

Published: Jan 1, 2013

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