Abstract

The current methods of searching and information retrieval are imprecise, often yielding results in tens of thousands of web pages. Extraction of the actual information needed often requires extensive manual browsing of retrieved documents. In order to address these drawbacks, this paper introduces an implementation in the field of food science of the ontology-based information retrieval system, and comparison is made with conventional information systems. The ontology of Food Semantic Web Knowledge Base (FSWKB) was built using the Protégé framework which supports two main models of ontology through the editors Protégé-Frames and Protégé-OWL. The FSWKB is composed of two heterogeneous ontologies, and these are merged and processed on a separate server application making use of the Apache Jena Fuseki an SPARQL server offering SPARQL endpoint. The experimental results indicated that ontology-based information systems are more effective in terms of their retrieval capability compared to the more conventional information retrieval systems. The retrieval effectiveness was measured in terms of precision and recall. The results of the work showed that traditional search results in average precision and recall levels of 0.92 and 0.18. The ontology-based test for precision and recall has average rates of 0.96 and 0.97.

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