Call for Papers

The rapid development of information and communication technologies (ICT) and the web completely transformed the tourism domain and created new online intermediaries competing and replacing traditional travel agents and agencies. Nowadays travelers actively search for information and compose their vacation packages according to their individual preferences. When onsite, they also predominantly rely on digital companions and tools  to plan, schedule and enjoy their stay.  

Recommender systems have thus developed to become indispensable tools for overcoming information overload and matching users with a wide variety of different tourism services such as transport, accommodation or activities and events. However, compared to, for instance, online commerce the tourism domain is substantially more complicated, and as such, creates huge challenges for those designing tourism-focused recommender systems. Planning a vacation usually involves searching for a set of products that are interconnected (e.g., means of transportation, lodging, attractions), with a rather limited availability, and where contextual aspects may have a major impact (e.g., time, location, social context, environmental context). In addition, products are emotionally “loaded” and considered experience goods; therefore, decision making is not only based on rational and objective criteria. As such, providing the right information to visitors of a tourism site at the right time about the site itself and various services nearby is challenging. 

RecTour 2022 will therefore focus on the specific challenges for recommender systems in tourism and will bring together researchers and practitioners from different fields, such as tourism, recommender systems, user modelling, user interaction, mobile, ubiquitous and ambient technologies, artificial intelligence and web information systems, to discuss and illustrate challenges and applications of these technologies in tourism recommender systems of the future. Important aspects and topics to be discussed revolve around (but are not limited to):

  • Specific applications and case studies (evaluation);
  • Specific methods and techniques for tourism recommenders;
  • Novel ICT and their impact on travel and tourism;
  • Data integration from various sources (e.g., catalogues, Linked Open Data, usage logs);
  • Context and mobility in tourism;
  • Tourist trip recommendation and route planning;
  • Cold-start problem in the context of tourism recommenders;
  • Preference elicitation in tourism;
  • Emotions and tourism recommenders;
  • Personalized interaction and conversation strategies;
  • Repercussions of COVID-19.