Co-located with the 10th ACM Conference on
Recommender Systems (RecSys 2016) This volume contains the contributions presented at the Workshop on Recommenders in Tourism (RecTour), hold in conjunction with the 10th ACM Conference on Recommender System (RecSys 2016), in Boston, MA, USA. RecTour 2016 focuses on the specific challenges for recommender systems in the tourism domain. In this domain, there are considerably more complicated scenarios than finding the best product for a user. Planning a vacation usu ally involves searching for a set of products that are interconnected (e.g. means of transportation, lodging, attractions etc.), with a rather limited availability, and where contextual aspects may have a major impact (spatiotemporal context, social context, environmental context). In addition and most importantly, products are emotionally “loaded” and therefore decision taking is not 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. Additionally and in contrast to many other domains, information providers are normally SMEs and do not have full information about available opportunities. Moreover, there is no single, standard format to house this information. Thus, given this diversity, building effective recommendation systems within the tourism domain is extremely challenging.
The rapid development of information and communication technologies (ICT) in general and the Web in particular, has transformed the tourism domain whereby travellers 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the site itself rather than renting a visitor guide that may be available, but considered to be expensive and sometimes outdated. However, like in many other cases, the blessing of the web comes with a curse – the curse of information overload. Recommender systems were suggested as 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.
The workshop aims at bringing together researchers and practitioners working in the tourism recommendation domain, in order to look at the challenges from the point of view of the user interactions as well as from the point of view of service providers and from the points of view of additional stakeholders as well (destination management organizations for instance). All in all, the workshop aims at attracting presentations of novel ideas for addressing these challenges and how to advance the current state of the art in this field. The primary goal of this workshop is to provide a forum for 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 explore various practical use cases of applications of these technologies in tourist recommender systems of the future. During the workshop we aim to identify the typical user groups, tasks and roles in order to achieve an adequate personalization and recommendation for tourism applications.
Workshop Committees
• Daniel Fesenmaier, University of Florida, USA. • Tsvi Kuflik, The University of Haifa, Israel • Julia Neidhardt, TU Wien, Austria Program Committee • Ulrike Gretzel, The University of Queensland, Australia • Antonio Moreno, Universitat Rovira i Virgili, Spain • Francesco Ricci, University of Bozen/Bolzano, Italy • Hannes Werthner, TU Wien, Austria • Wolfgang Wörndl, Technische Universität München, Germany • Zheng Xiang, Virginia Tech, USA • Markus Zanker, University of Bozen/Bolzano, Italy
Workshop Program 14:00 - 15:30 Session 3 14:00 - 15:00 Research papers: Advanced topics in tourism recommender systems • Amra Delic, Julia Neidhardt, Thuy Ngoc Nguyen and Francesco Ricci: Research Methods for Group Recommender Systems. • Paula Saavedra, Pablo Barreiro, Roi Durán, Rosa Crujeiras, María Loureiro and Eduardo Sánchez Vila: Choicebased recommender systems. 15:00 - 15:30 Demo papers: Event recommendations • Stacey Donohue, Nevena Dragovic and Maria Soledad Pera: Anything Fun Going On? A Simple Wizard to Avoid the Cold-Start Problem for Event Recommenders. • Sean MacLachlan, Nevena Dragovic, Stacey Donohue and Maria Soledad Pera: “One Size Doesn’t Fit All”: Helping Users Find Events from Multiple Perspectives. 15:30 - 16:00 Demo session/Coffee break 16:00 - 17:30 Session 4 16:00 - 16:45 Position papers: Further research challanges • Jan Fabian Ehmke, Dirk Christian Mattfeld and Linda Albrecht: Combining Mobility Services by Customer-Induced Orchestration. • Daniel Herzog and Wolfgang Wörndl: Exploiting Item Dependencies to Improve Tourist Trip Recommendations. • Manoj Reddy Dareddy: Challenges in Recommender Systems for Tourism. 16:45 - 17:30 Panel discussion and workshop summary Panel discussion: Specific challenges for recommender systems in the tourism domain. • Daniel Fesenmaier, University of Florida, USA • Hannes Werthner, TU Wien, Austria • Wolfgang Wörndl, Technische Universität München, Germany
• Mesut Kaya and Derek Bridge: Improved Recommendation of Photo-Taking Locations using Virtual Ratings. 1 - 7 • Patrick Hiesel, Matthias Braunhofer and Wolfgang Wörndl: Learning the Popularity of Items for Mobile Tourist Guides. 8 - 15 • Christoph Trattner, Alexander Oberegger, Lukas Eberhard, Denis Parra and Leandro Balby Marinho: Understanding the Impact of Weather for POI Recommendations. 16 - 23 • Khadija Vakeel and Sanjog Ray: A Motivation-Aware Approach for Point of Interest Recommendations. 24 - 29 • Amra Delic, Julia Neidhardt, Thuy Ngoc Nguyen and Francesco Ricci: Research Methods for Group Recommender Systems. 30 - 37 • Paula Saavedra, Pablo Barreiro, Roi Durán, Rosa Crujeiras, María Loureiro and Eduardo Sánchez Vila: Choicebased recommender systems. 38 - 46
• Stacey Donohue, Nevena Dragovic and Maria Soledad Pera: Anything Fun Going On? A Simple Wizard to Avoid the Cold-Start Problem for Event Recommenders. 47 - 48 • Sean MacLachlan, Nevena Dragovic, Stacey Donohue and Maria Soledad Pera: “One Size Doesn’t Fit All”: Helping Users Find Events from Multiple Perspectives. 49 - 50