UMBC ebiquity
Text Based Similarity and Delta for Semantic Web Graphs
August 7, 2010
Recognizing that two Semantic Web documents or graphs are similar, and characterizing their differences is useful in many tasks, including retrieval, updating, version control and knowledge base editing. We describe a number of text based similarity metrics that characterize the relation between Semantic Web graphs and evaluate these metrics for three specific cases of similarity that we have identified: similarity in classes and properties used while differing only in literal content, difference only in base-URI, and versioning relationship. When one graph is judged to be a version of another, we generate a “delta” consisting of of triples to be added or removed from one graph to make them equivalent. This method takes into account the text of the RDF graph’s serialization as a document, rather than relying solely on the document URI. We have prototyped these techniques in a system that we call Similis and evaluated its performance on several tasks using a collection of graphs from the archive of the Swoogle Semantic Web search engine.
TechReport
University of Maryland, Baltimore County
Computer Science and Electrical Engineering
1000 Hilltop Circle
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