Automated Generation of Itineraries in Recommender Systems for Tourism

Current recommender systems can support tourists in choosing travel products (accommodation, activities, means of transport, etc.), in planning long trips, and in profitably spending time in a specific geographical area such as a region (or a city). In the last case, the system should be able to construct itineraries suited to the tourist’s interests. In this paper, a method for generating tourist itineraries in knowledge-based recommender systems is proposed. The method is based on a theoretical model that defines space-time relations among items of intangible cultural heritage (called events) and on transitive closure computation (of the relations), that is able to construct chains of events. The proposed method has been implemented in the T-Path recommender system, that suggests itineraries of cultural events occurring in the Apulia region

NightSplitter: a scheduling tool to optimize (sub)group activities

International audienceHumans are social animals and usually organize activities in groups. However, they are often willing to split temporarily a bigger group in subgroups to enhance their preferences. In this work we present NightSplitter, an on-line tool that is able to plan movie and dinner activities for a group of users, possibly splitting them in subgroups to optimally satisfy their preferences. We first model and prove that this problem is NP-complete. We then use Constraint Programming (CP) or alternatively Simulated Annealing (SA) to solve it. Empirical results show the feasibility of the approach even for big cities where hundreds of users can select among hundreds of movies and thousand of restaurants

A Model for Generating Tourist Itineraries

A challenge in the recommender systems currently available for the tourism domain is how to suggest tourist itineraries in a specific geographical area (city or region). The proposed theoretical model allows items of intangible cultural heritage (events) such as processions, festivals, special markets, etc. to be characterized and correlated. The model features both a set of functions characterizing the events and a space-time relation that defines whether two events are correlated. The model allows itineraries to be constructed by computing the transitive closure of the space-time relation on the set of events. It can be used to construct itineraries at different grain sizes. This capacity makes the model scalable and easily applicable in the development of several applications. It has been implemented in a first order logic knowledge base in order to make an empirical evaluation of the model