RDF Link Generation by Exploring Related Links on the Web of Data
Author(s) -
Kumar Sharma,
Ujjal Marjit,
Utpal Biswas
Publication year - 2018
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2018.10.08
Subject(s) - rdf , computer science , linked data , semantic web , web resource , sparql , rdf schema , cwm , task (project management) , information retrieval , rdf/xml , resource (disambiguation) , social semantic web , matching (statistics) , data web , semantic analytics , world wide web , web service , computer network , statistics , mathematics , management , economics
Interlinking RDF resources is a vital aspect of the Semantic Web technology. It is the basis of Linked Data that provides interlinked datasets on the web. One of the principles of Linked Data is interlinking resources from different data sources on the web. Data interlinking is a critical and challenging problem that every Linked Data generation applications face. Various approaches have been evolved for resolving this problem, but, for more massive datasets, it becomes almost indefinite time while linking similar or related resources. Linking RDF resources is like the problem of entity matching, record matching or duplicate resource detection. More or less they attempt to point to the same problem, but the RDF link generation is the task of finding related resources on the web. In this article, we present an approach for generating RDF links using the similarity measure between two RDF resources and by exploring associated relationships of the matched resources. The idea is to find related resources and link them with an RDF resource that is being generated.
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