Collaborative filtering technique based recommendation in ubiquitous commerce

Ubiquitous commerce (u-commerce) is an emerging area of ubiquitous computing. Electronic commerce (e-commerce), mobile commerce (m-commerce), and ubiquitous commerce are based not only on development concerns of Internet but also technological and organizational innovations arising from the combination of telecommunications and organizational computing. In u-commerce, service is provided according to user´s personal profile, which includes individual user´s preference by considering the technical limitation of mobile device. In ubiquitous environment, a recommender system plays an important role which is mainly used to provide the suitable recommendations to the user. This paper proposes a new smart computing environment for retail chain management. The proposed system uses ubiquitous commerce for recommendation of products. At the basic level of design, consideration of user ratings, historical ratings, and absence of rating values (those who are not given the rating of the products for prediction). Initially, the value of product is set to zero that is not rated by any user. The proposed system recommends the predicted item to users. Finally, we have evaluated the performance parameters for the proposed scheme in terms of recommendation time, prediction time, end to end delay, error prediction, and throughput.