K-Radius Subgraph Comparison for RDF Data Cleansing

With the quick development of the semantic web technology, RDF data explosion has become a challenging problem. Since RDF data are always from different resources which may have overlap with each other, they could have duplicates. These duplicates may cause ambiguity and even error in reasoning. However, attentions are seldom paid to this problem. In this paper, we study the problem and give a solution, named K-radius subgraph comparison (KSC). The proposed method is based on RDF-Hierarchical Graph Model. KSC combines similar and comparison of context to detect duplicate in RDF data. Experiments on publication datasets show that the proposed method is efficient in duplicate detection of RDF data. KSC is simpler and less time-costs than other methods of graph comparison.

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