Simple Algorithms for Predicate Suggestions Using Similarity and Co-occurrence

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 convergerce 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.

• Type: Conference
• Year: 2007
• Where: ESWS
• Authors: Eyal Oren, Sebastian Gerke, Stefan Decker
• Keywords: Collaborative Tagging Environments, ESWS 2007, Mechanisms Help Terminology, Prevents Terminology Divergence