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. © 2012 Springer-Verlag.
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CITATION STYLE
Zong, N., Yang, S., Namgoong, H., & Kim, H. G. (2012). Discovering and ranking new links for linked data supplier. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7185 LNCS, pp. 358–365). https://doi.org/10.1007/978-3-642-29923-0_25
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