Situation awareness for recommender systems

Christian Richthammer () and Günther Pernul
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Christian Richthammer: University of Regensburg
Günther Pernul: University of Regensburg

Electronic Commerce Research, 2020, vol. 20, issue 4, No 5, 783-806

Abstract: Abstract One major shortcoming of traditional recommender systems is their inability to adjust to users’ short-term preferences resulting from varying situation-specific factors. To address this, we propose the notion of situation-aware recommender systems, which are supposed to autonomously determine the users’ current situation based on a multitude of contextual side information and generate truly personalized recommendations. In particular, we develop a situation awareness model for recommender systems, include it in a situation-aware recommendation process, and derive generic design steps for the design of situation-aware recommender systems. The feasibility of these concepts is demonstrated by directly employing them for the development and implementation of a music recommender system for everyday situations. Moreover, their meaningfulness is shown by means of an empirical user study. The outcomes of the evaluation indicate a significant increase in user satisfaction compared to traditional (i.e. non-situation-aware) recommendations.

Keywords: Recommender systems; Situation awareness; Context awareness; Contextual side information; Situation-aware recommender systems (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10660-018-9321-z

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