| Abstract: | Recently, an ever increasing number of e‐Commerce tools has been made available that are able to help customers by generating purposed recommendations. Many of them are centralized so that they have to face problems related to efficiency and scalability. A few of them are distributed, but in this case, the complexity of the e‐Commerce process implies computation overhead on the client side, which is often unsuitable if mobile devices are used by customers. In this paper, we study how the software distribution in recommender systems affects their performances, depending on the characteristics of the e‐Commerce population. To this end, we present a distributed testbed architecture for e‐Commerce recommender systems using a multi‐tiered agent‐based approach to generate effective recommendations without requiring such an onerous amount of computation per single client. We use such a testbed to study the main advantages and limitations associated with the problem of distributing the computation of recommendations. Copyright © 2016 John Wiley & Sons, Ltd. |
