Turist@: Agent-based personalised recommendation of tourist activities Montserrat Batet, Antonio Moreno, David Sánchez ⇑ , David Isern, Aïda Valls Departament d’Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Av. Països Catalans, 26. 43007 Tarragona, Catalonia, Spain article info Keywords: Multi-agent systems Recommender systems Tourism abstract Recommender systems in e-Tourism normally focus on helping tourists to select appropriate destina- tions. A related problem that has been less explored in the literature is how to provide personalised rec- ommendations of cultural and leisure activities when the tourist has already arrived at the destination. This paper presents a novel recommendation system, Turist@, which addresses this issue. Its agent-based modular design permits to model different kinds of activities in a flexible way, and allows the implemen- tation of a location-aware front-end in the mobile device of the user. Special care has been put in the rec- ommendation engine, implemented via a specialised Recommender Agent. It incorporates a mixture of content-based and collaborative recommendation strategies, thus avoiding the drawbacks of each indi- vidual method, and is able to perform recommendations in heterogeneous scenarios. Recommendations take into account user profiles which are implicitly updated after the analysis of user actions (e.g., que- ries, evaluations). The system has been successfully deployed and tested in the World Heritage-listed city of Tarragona. Ó 2012 Elsevier Ltd. All rights reserved. 1. Introduction Tourism has experienced an enormous growth in recent years, motivated, in part, for the fast development of information and com- munication technologies and the global spread of Internet (Alptekin & Büyüközkhan, 2011), which have eased the access to large amounts of information about destinations, points of interest and travelling plans to potential tourists all around the world. Nowadays, e-Tourism (Castillo et al., 2008) enjoys a great success both from an economic and a social perspective. Many electronic sites and Web portals offer up-to-date information which is massively used by tourists to select destinations and plan their trips. Due to the obvious interest of both tourists and destination providers in selecting enjoy- able destinations, and taking into account the overwhelming amount of information available through the Web, many recom- mender systems have been developed to assist in the process of choosing travel destinations and planning tourist trips (see an over- view in Section 2). Considering that Tourism is an activity strongly connected to personal preferences and interests (Garcia, Sebastia, & Onaindia, 2011), recommender systems usually rely on ratings and opinions of previous users to suggest possible destinations. As will be shown in the related work section, most of the recommender systems that have been developed in the last years focus on the analysis and comparison of tourist destinations, to help the user to select the most appropriate one. However, it is also of great importance for the user to be aware of the specific attrac- tions that can be visited when he/she has already arrived at a particular destination. Information about points of interest and cultural and leisure activities is very dynamic and, in many cases, difficult to retrieve, analyse and filter. On-site dynamic recommen- dations play an important role both for the tourist, who is inter- ested in attractions that he/she may enjoy according to his/her personal profile, and for the destination provider, who is interested in increasing the visibility of the available attractions, especially in the case of low-profile activities in popular destinations, an impor- tant aspect of the so called sustainable Tourism (Borrás et al., 2011). In recent years, a scarce number of tourism recommender systems have focused on this aspect. Unlike the above-mentioned systems, these approaches should face, in addition to the profile-based recommendation task, other related issues such as the retrieval and appropriate consideration of the user’s constraints during the stay (e.g., in aspects like budget, accessibility, language or agenda), the dynamic determination of the user’s position and its integra- tion in a location-aware recommendation process (i.e., geo-locali- sation of the user and the points of interest), and the inclusion of a desirable high degree of proactivity and dynamicity in order to adapt the system’s suggestions to the behaviour of the user at the destination (Castillo et al., 2008). The system presented in this paper is framed in this context and it has been designed with the following main goals in mind: (i) to provide an easy and ubiquitous access to the desired information about tourist attractions, (ii) to provide proactive recommenda- tions of attractions by means of a hybrid recommendation system that considers elements such as the user profile and preferences, 0957-4174/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.eswa.2012.01.086 ⇑ Corresponding author. Tel.: +34 977256563; fax: +34 977559710. E-mail addresses: montserrat.batet@urv.cat (M. Batet), antonio.moreno@urv.cat (A. Moreno), david.sanchez@urv.cat (D. Sánchez), david.isern@urv.cat (D. Isern), aida.valls@urv.cat (A. Valls). Expert Systems with Applications 39 (2012) 7319–7329 Contents lists available at SciVerse ScienceDirect Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa