Research on logistics service recommendation model and application under mobile cloud environment

Abstract

Today's personal computer applications are mainly cloud computing services, but it is usually inevitable to apply cloud computing to mobile cloud environments. Computing in the mobile cloud environment has the following advantages: more resources, free access to the "cloud" through any device anytime and anywhere, and provides powerful functions for computer storage and computing, while meeting the needs of more convenient software services. It has become the focus of attention in the last two years. Logistics service quality is an important indicator to measure service quality and reflects customer satisfaction with service. This is very important for service users and logistics providers. However, at present, there is a lack of unified judgment standards for the measurement of logistics service quality, and different scoring systems have different points of emphasis, so users can't get effective recommendation when choosing products. Therefore, this paper applies the principle of mobile cloud environment, combines the evaluation of logistics service quality with the big data system, selects the appropriate logistics service according to the needs of users, and recommends it to users, so as to provide more powerful assistance for users to choose products and improve the efficiency of product selection.This article introduces the recommendation model design, analyzes the complete update problem of the traditional recommendation model, proposes the incremental update recommendation model design, and implements it in a distributed manner on the basis of the Hadoop cloud computing platform.