The rapid development of information and communication technologies (ICT) and the web transformed the tourism domain. Today, travelers no longer rely on travel agents/agencies. Indeed, recent studies indicate that they are now active in searching for information and composing their vacation packages according to their specific preferences. When onsite, they search for freely available information about the site itself rather than buying/renting a visitor guide or hiring a tour guide that may be available. However, like in many other cases, the blessing of the Web comes with a curse – the curse of information overload.
Recommender systems are a practical tool for overcoming this information overload. However, 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 taking is not only based on rational and objective criteria (i.e., system 2 thinking). 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 2019 will focus on the specific challenges for recommender systems in tourism and will bring together researchers and practitioners from different fields, e.g., 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;
- Integrating data from various sources (e.g., catalogues, Linked Open Data, and 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;
- Interaction concepts with personal (mobile or desktop) and group (on-site public or desktop) displays;
- Information needs, information access (including visualisation) and search patterns;
- Collaboration, communication and sharing aspects in the process of tourist information consumption;
- Personalized explanations and feedback of recommendation systems;
- Digital storytelling, narratives, smart summaries and recommendation explanations.