Dynamic Ontology-based Travel Recommendation System

The growth of personalized travel services calls for sophisticated systems to deliver tailored recommendations based on user preferences and real-time contextual data. The paper presents a Dynamic Ontology-Based Travel Recommendation System that uses semantic web technologies to give personalized travel suggestions. To achieve this, the system has integrated ontology based on travel-related concepts such as destinations, activities, accommodations, and user preferences, facilitating complex querying and reasoning to make recommendations. This is achieved through dynamic content integration, including real-time data updates from external sources and user interactions, making it a responsive system for changing conditions. Moreover, fuzzy matching and ontology merging techniques have been incorporated into the system to effectively deal with uncertainty and combine multiple knowledge sources. Consequently, apart from enhancing the relevance and personalization of travel recommendations, the proposed system also provides explainable suggestions, building user trust and satisfaction.