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.
It is the goal of this workshop to bring together researchers from the fields of recommender systems, pervasive computing, mobile computing, urban sensing, social networking, context-aware systems and...
For a List of RSS 2.0 Feeds: Please Click Here