Abstract
In this paper we analyze users' preferences for Points of Interest (POIs), before and after the POIs are experienced: these are called expected and experienced utilities. State-of-the-art research in other domains, has shown that the difference between the user's expected utility, which is estimated at the choice stage, and the experienced utility, obtained after the consumption of the item, is domain dependent. This discrepancy is here measured in the tourism domain by focusing on the POI recommendation problem. We have designed and implemented an interactive web-based survey to collect the two types of utility data. The analysis of the data collected from a sample of users shows that the two utilities express quite different preferences. This result may be exploited to design novel POI recommendation models that can optimally leverage both types of preference signals.
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CITATION STYLE
Hofschen, K., Massimo, D., & Ricci, F. (2023). Expected and Experienced Utility of Points of Interest in Tourism Recommender Systems. In UMAP 2023 - Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (pp. 50–55). Association for Computing Machinery, Inc. https://doi.org/10.1145/3563359.3597405
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