Utilising Crowd Information of Tourist Spots in an Interactive Tour Recommender System

Although the congestion of tourist spots has a huge effect on tourist experiences, few studies have discussed crowd information in the research field of recommender systems for tour planning. This study developed a recommender system that utilises crowd information interactively to support tour planning. The study created a bar graph about relative crowdedness in a day based on the idea that the measures required for a crowd vary depending on each tourist. This research conducted user experiments to examine how tourists are conscious of crowds. The proposed system can provide alternative plans in 70% of cases when tourists wish to visit a spot when it is not crowded. Furthermore, the results imply the importance of focusing on differences in tourists with regard to a sightseeing spot. The sightseeing experiences of tourists may be enhanced by conducting expectation management for sightseeing using ICT.

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