Abstract—Abstract—This paper presents a semi-automatic recommendation-based instance matching system using RDF graph data. Based on a graph node similarity algorithm, our instance matching system detects instance nodes with similarities higher than an input threshold value and returns to the user the subject node pairs. The system merges a matched node pair when the user confirms the matched nodes in the results. After a merge, the merged node is also considered as an entity for the following candidate pair generation cycle. The procedure continues until no new matching candidate pairs are recommended by the algorithm and there is no more feedback provided by the user.
Index Terms—Index Terms—Instance Matching, RDF, Semantic Web, Similarity Metrics.
M. Aydar is with the Department of Computer Science, Kent State University, Kent, OH 44240 USA (e-mail: maydar@ kent.edu).
S. Ayvaz is with Department of Software Engineering, Bahcesehir University, Besiktas 34353, Istanbul, Turkey (Corresponding author; e-mail: serkan.ayvaz@eng.bau.edu.tr).
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Cite:Mehmet Aydar and Serkan Ayvaz, "A Suggestion-Based RDF Instance Matching System," International Journal of Computer Theory and Engineering vol. 9, no.5, pp. 380-384, 2017.
