Simple Algorithms for Predicate Suggestions Using Similarity and Co-occurrence

Authors:
Eyal Oren;Sebastian Gerke;Stefan Decker
Affiliations:
Digital Enterprise Research Institute, National University of Ireland, Galway, Galway, Ireland;Digital Enterprise Research Institute, National University of Ireland, Galway, Galway, Ireland;Digital Enterprise Research Institute, National University of Ireland, Galway, Galway, Ireland
Venue:
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Year:
2007

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Abstract

When creating Semantic Web data, users have to make a critical choice for a vocabulary: only through shared vocabularies can meaning be established. A centralised policy prevents terminology divergence but would restrict users needlessly. As seen in collaborative tagging environments, suggestion mechanisms help terminology convergence without forcing users. We introduce two domain-independent algorithms for recommending predicates (RDF statements) about resources, based on statistical dataset analysis. The first algorithm is based on similarity between resources, the second one is based on co-occurrence of predicates. Experimental evaluation shows very promising results: a high precision with relatively high recall in linear runtime performance.