A multi-agent recommender system for supporting device adaptivity in E-commerce

E-Commerce recommender systems provide customers with useful suggestions about available products. However, in presence of a high number of interactions between customers and Web sites, the generation of recommendations can become a heavy task. Moreover, customers often navigate on the Web using different devices whose different characteristics may influence customer's preferences. In this paper we propose a new multi-agent system in which each device exploited by a customer is associated with a software agent which autonomously monitors the customer's behaviour. The use of device agents leads to generate recommendations taking into account the exploited device, while the fully decentralized architecture introduces a strong reduction of the time costs.