In this paper, we propose a ubiquitous product rating system. First we provide an overview of state-of-the-art product recommendation, concluding that current approaches do not support in-store consumers; i.e. consumers on the shop floor. Within shops however is where three out of four buying decisions are made. Hence we propose APriori, a new approach towards mobile product recommendation. APriori makes product recommendation available for mobile users. These utilize their phones to identify tagged (barcode/RFID) consumer products. Based on the identification of products, the mobile device communicates with a backend product recommendation system. As a new rating concept we propose the use of user-generated rating criteria. Accordingly, we describe the APriori prototype implementation and first user experiences. We conclude with discussions about future research directions.
The 3rd International Conference on the Internet of Things (IoT2012) will include a highly selective dual-track program for technical papers, accompanied by reports on business projects from seasoned ...
Mark Weiser first proposed Pervasive Computing two decades ago and we've explored the space of his ideas in that time. It's time to explore new wild and crazy -- "hot" -- ideas! The goal of PerHot is ...
As part of their research for GS1, members of the Auto-ID Labs research network have presented a recent update at GS1's Industry and Standards Event in Brooklyn, March 2011.
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