Interest-Satisfaction Estimation Model for Point-of-Interest Recommendations in Tourism

摘要

Today, the Internet and the Web coupled with mobile applications enable tourists to access more information related to tourism than ever before. Due to information overload, it is very complex and time consuming for tourists to discern and decide on destinations that match better with their interests. Recommender Systems which filter information efficiently come to their rescue and recommend personalized and more appealing destinations based on their preferences. However, building high-quality recommender systems in tourism domain remains a pertinent research problem due to several reasons. Towards this end, we propose a novel approach that exploits multi-criteria decision-making and information filtering to recommend destinations that are most aligned to a tourist's preferences. Our assessment suggests that the approach effectively addresses the problem, improves tourist's satisfaction and consequently helps promote tourism.