LinkD: element-based data interlinking of RDF datasets in linked data

Kettouch, Mohamed Salah and Luca, Cristina (2022) LinkD: element-based data interlinking of RDF datasets in linked data. Computing. ISSN 1436-5057

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Abstract

One of the main obstacles in publishing in a Linked Data way is to connect the dataset being published externally with related data sources in the cloud, known as Data Interlinking. This paper proposes LinkD, a new element-based interlinking approach. LinkD interlinks an RDF dataset, resulted from transformed semi-structured data, with its counterparts in the web of Linked Data. To provide similarity links, the existence of published data in the Linked Data cloud is done in the first place. Different algorithms for similarity measurement are employed while the domain of the dataset being interlinked is taken into account. The techniques utilised allow the processing of a large number of Linked Data datasets. The evaluation of LinkD shows high precision, recall and performance.

Item Type:	Journal Article
Keywords:	Data interlinking, Linked Data, Link Discovery, Semi-structured Data, Instance Matching, Semantic Web
Faculty:	Faculty of Science & Engineering
SWORD Depositor:	Symplectic User
Depositing User:	Symplectic User
Date Deposited:	02 Aug 2022 16:30
Last Modified:	02 Aug 2022 16:30
URI:	https://arro.anglia.ac.uk/id/eprint/707782

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