Generating multi-day round trip itineraries for tourists

Recommender systems facilitate the decision making process for users by selecting and ranking items according to users' interests. Travellers can highly benefit from recommender systems due to vast amount of information available regarding places to visit and many different factors that affect the travel plans. Travel recommender systems tackle both the issues of recommending relevant places and also sequencing them in a feasible order. However there are many different constraints that affect the recommendations for travellers such as travel dates, weather and companions, which makes the recommendation system more complex. In this paper, we present a novel approach to create multi-day trips that start and end at the accommodation of the user. We apply different clustering algorithms to tackle the issue of creating multi-day trips with balanced itineraries and conduct a user study to understand how our approach performed against baseline methods. Our results show that our algorithm performs better than other selected methods to recommend interesting points-of-interests to users and create appealing itineraries.