Towards Attentive In-Store Recommender Systems

We present research-in-progress on an attentive in-store mobile recommender system that is integrated into the user’s glasses and worn during purchase decisions. The system makes use of the Attentive Mobile Interactive Cognitive Assistant (AMICA) platform prototype designed as a ubiquitous technology that supports people in their everyday-life. This paper gives a short overview of the technology and presents results from a pre-study in which we collected real-life eye-tracking data during decision processes in a supermarket. The data helps us to characterize and identify the different decision contexts based on differences in the observed attentional processes. AMICA provides eye-tracking data that can be used to classify decision-making behavior in real-time to make a recommendation process context-aware.

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