Discovering and ranking new links for linked data supplier

Authors:
Nansu Zong;Sungkwon Yang;Hyun Namgoong;Hong-Gee Kim
Affiliations:
Biomedical Knowledge Engineering Lab. School of Dentistry, Seoul National University, Korea;Biomedical Knowledge Engineering Lab. School of Dentistry, Seoul National University, Korea;Biomedical Knowledge Engineering Lab. School of Dentistry, Seoul National University, Korea;Biomedical Knowledge Engineering Lab. School of Dentistry, Seoul National University, Korea
Venue:
JIST'11 Proceedings of the 2011 joint international conference on The Semantic Web
Year:
2011

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Abstract

For new data supplier who wants to join the web of data club, it's difficult to find new links between local repository and data sets in the web of data to make local data well-connected or harmonize with other data. The purpose of this research is not for finding similar entities but discovering new potential link for helping users have more choice for using multiple links instead of only using "owl:sameAs". The approach use information retrieval technique index the data sets and Page Rank and graph theory analyze RDF document to filter links. We implemented our method using Dbpedia data sets and two open ontologies, the results showed our approach can discover new links with highly accuracy.