SemCoTrip: A variety-seeking model for recommending travel activities in a composite trip

Abstract

Selecting appropriate activities, especially in multi-destinations trips, is a hard task that many travellers face each time they want to plan for a trip. With the budget and time limitations, travellers will try to select activities that best fit their personal interests. Most of existing travel recommender systems don’t focus on activities that a traveller might be interested in. In this paper, we go beyond the specific problem of combining regions in a composite trip to propose a variety-seeking model which is capable of providing travelllers with recommendations on what activities they can engage in when visiting different regions. A semantical hierarchical clustering-based model is proposed to guarantee diversity within the set of recommended activities. Experimental results on a real dataset have shown that the proposed approach helps the traveller to avoid doing the same or similar activities in a composite trip, thus, promoting less popular activities to be selected.