Ontology-based approaches for multi-destination tourism planning: a systematic literature review

Tourism planning is becoming increasingly complex as travel behavior shifts from single-destination visits to multi-destination itineraries. However, many tourism information systems still rely on point-of-interest data and recommendation algorithms that lack the semantic structures needed to represent relationships between destinations. This limitation is important in smart tourism environments that require interoperable, data-integrated systems to support meaningful travel planning. This study conducts a systematic literature review of ontology and knowledge graph-based approaches for tourism planning to assess their ability to support itinerary modelling. Using PRISMA guidelines, relevant studies were retrieved from Scopus, ScienceDirect and IEEE Xplore, with 21 articles meeting all eligibility criteria. The review identifies six themes: ontology and semantic modelling, knowledge graph construction and enrichment, tourism recommendation and personalization, semantic retrieval and question answering, route planning and decision support, and itinerary-level and multi-destination representation. The analysis shows that ontology and knowledge graphs are widely used to organize tourism knowledge and enhance recommendation systems. However, most studies remain focused on entity-level modelling, while explicit semantic modelling of itinerary-level constructs remains limited. This gap highlights the need for ontology frameworks that can formally represent travel sequences and inter-destination dependencies to better support smart-tourism planning.