Inf Technol Tourism (2018) 19:83–85 https://doi.org/10.1007/s40558-018-0111-1 EDITORIAL 1 2 3 Julia Neidhardt · Tsvi Kuflik · Wolfgang Wörndl Received: 7 April 2018 / Accepted: 11 April 2018 / Published online: 17 April 2018 © Springer-Verlag GmbH Germany, part of Springer Nature 2018 The focus of this special section is on the specific challenges for recommender sys - tems in tourism. The common task of classical recommender systems is to find the best (single) product for a user, but in the domain of tourism, the scenario is con- siderably more complex. Planning a vacation usually involves searching for a rea- sonably large 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., spatiotemporal context, social context, environmen- tal context). In addition and most importantly, products are emotionally “loaded” and therefore decision taking is not based only on rational and objective criteria (Werthner and Ricci 2004). 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 chal- lenging. Additionally, and in contrast to many other domains, information providers are normally small–medium enterprises
Information Technology & Tourism – Springer Journals
Published: Apr 17, 2018
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