Details

Autor(en) / Beteiligte

• Formica, Anna
• Missikoff, Michele
• Pourabbas, Elaheh
• Taglino, Francesco

Titel

A Bayesian Approach for Semantic Search Based on DAG-Shaped Ontologies

Ist Teil von

• Database and Expert Systems Applications, p.126-140

Ort / Verlag

Cham: Springer International Publishing

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Semantic search has a great potentiality in helping users to make choices, since it appears to outperform traditional keyword-based approaches. This paper presents an ontology-based semantic search method, referred to as influential SemSim (i-SemSim), which relies on the Bayesian probabilistic approach for weighting the reference ontology. The Bayesian approach seems promising when the reference ontology is organized according to a Directed Acyclic Graph (DAG). In particular, in the proposed method the similarity among a user request and semantically annotated resources is evaluated. The user request, as well as each annotated resource, is represented by a set of concepts of the reference ontology. The experimental results of this paper show that the adoption of the Bayesian method for weighting DAG-based reference ontologies allows i-SemSim to outperform the most representative methods selected in the literature.