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CJICT: VOL. 9 N0. 1, JUNE 2021

Restaurant Multi-Context-Based Information Retrieval System Ontological Model

  • Nnebe Samuel Ekene
  • Okoro Efeosasere Moibi
  • Abara Benjamin Abaioni
June 29, 2021


This paper aims to improve information retrieval results by considering multi-context-based information that can be associated with retrieval. Traditional Information Retrieval has been termed inefficient because of its lack of consideration for individual user preference and contexts. An example domain where user preference and context consideration are expedient is the restaurant and food information retrieval domain. Current food-based ontologies do not provide sufficient information to tackle this challenge. We analysed existing food-based ontologies, developed and evaluated a restaurant-food-based ontology that provides application developers with a formalised restaurant-food ontology that will foster interoperability and information sharing within the domain. The ontology was developed using the methontology methodology for ontology development. Our restaurant-food ontology is based on ontology web language (OWL) and implemented in Protégé ontology editor. Using standard ontology evaluation measures of competency (in terms of precision and recall) and consistency, our results show that our ontology is 100% competent and can be used to build a range of applications that require answering a wide range of queries correctly that are general, detailed, context-based (location and environmental) and preference-based. This is currently, beyond what traditional Information retrieval and location-based systems can answer with accuracy