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Text Based Similarity Metrics and Delta for Semantic Web Graphs

Description: 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.

In addition to determining the similarity between two Semantic Web graphs, we generate a ’delta’ between graphs that have been identified as having a versioning relationship. The delta consists of triples to be added or removed from one 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.

Type: Presentation

Authors: Krishnamurthy Viswanathan

Date: November 30, 1999

Tags: semantic web, rdf, information retrieval, ontology

Format: Microsoft PowerPoint (Need a reader? Get one here)

Number of downloads: 463

Access Control: Publicly Available

 

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  1. (Resource) Text Based Similarity Metrics and Delta for Semantic Web Graphs is the PowerPoint slides of (Event) Text Based Similarity Metrics and Delta for Semantic Web Graphs