Tourism Destination Recommendation Using Ontology-based Conversational Recommender System

Abstract

Traveling is one of the human psychological needs. Many choices and lack of information about desired tourist attractions are some of the obstacles in fulfilling the need. One of the technologies to overcome these obstacles is the recommender system which can provide recommendations for the users to choose some interesting tourist attractions from several tourist destinations. A conversational recommender system (CRS) offers a way of recommending tourist destinations in a conversational mechanism. We use ontology as a representation of knowledge to generate conversational interactions, recommendations, and explanation facilities. With this ontology-based CRS, we can overcome cold start problems, and also the system can guide the users to get the desired tourist attractions. In this study, we use a combination of navigation by asking (NBA) and navigation by proposing (NBP) strategy to generate interactions on the CRS. Based on the user study, in general, users find it helpful in finding tourist destinations that suit their needs. It is because the factor of trust and perceived ease of use comes from the interaction and explanation facilities contained in the system. Besides, perceived usefulness directly affects users' interest in utilizing this CRS interaction model in the future.

SmartTur+ECO: a conversational recommender system for tourism

“…Ontologies have been used in RS to refine the user model with more specific tourist preferences (Moreno et al (2013)). In the context of CRSs, some researchers exploit ontologies as knowledge representation to generate conversational interactions, recommendations, and explanation facilities for suggesting tourist attractions (Baizal et al (2021)). Reinforcement Learning techniques have also been shown to be useful in learning autonomously an adaptive interaction strategy that is suited for online travel planning recommendations (Mahmood et al (2008)).…”

Healthy Food Recommender System for Obesity Using Ontology and Semantic Web Rule Language

“…We created a recommender system to recommend healthy menus using ontology and Semantic Rule Web Language (SWRL) in this study. Ontology is widely used as a representation of knowledge in knowledge-based recommender systems, such as for tourism recommendations [12], query functional refinement in a conversational recommender system [13], consumer product recommendations by utilizing high-level requirements [14], and laptop recommendations based on product functional requirements [15].…”

Chatbot for Knowledge – Based Museum Recommender System (Case Study: Museum in Jakarta)

“…Ontology is one of the knowledge representations that is often used in the development of knowledge-based recommender system [6]. Center for Intercultural Documentation Conceptual Reference Model (CIDOC CRM) is an ontology that is often used for cultural heritage domain such as museum, because it is the standard ontology for cultural heritage domain [7].…”