A Study of Situated Product Recommendations in Augmented Reality

2018 
Augmented Reality interfaces increasingly utilize artificial intelligence systems to tailor content and experiences to the user. We explore the effects of one such system - a recommender system for online shopping - which allows customers to view personalized product recommendations in the physical spaces where they might be used. We describe results of a 2x3 condition exploratory study in which recommendation quality was varied across 3 user interface types. Our results highlight potential differences in user perception of the recommended objects in an AR environment. Specifically, users rate product recommendations significantly higher in AR and in a 3D browser interface, and show a significant increase in trust in the recommender system, compared to a web interface with 2D product images. Through semi-structured interviews, we gather participant feedback which suggests AR interfaces perform better due to their ability to view products within the physical context where they will be used.
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