Design and Evaluation of an Ontology-Based Context-Aware System for Advertising Recommendations

This research focuses on the design and evaluation of an ontology-based context-aware system for advertising recommendations. The study addresses the limitations of traditional advertising systems, which often neglect key contextual factors such as user location, time, and needs. Using the NeOn methodology, the proposed ontology incorporates these contextual dimensions, integrating widely accepted ontologies like FOAF, OWL-Time, and WGS84 Geo Positioning. The developed ontology was tested using SPARQL and GeoSPARQL queries to ensure it could accurately represent advertising and contextual information, delivering relevant recommendations tailored to users' current situations. The results demonstrate the ontology's scalability, expressiveness, and effectiveness in providing context-aware advertising recommendations. Future work includes developing a mobile application that leverages the ontology to enhance real-time advertising recommendations.