Analysis of a context-aware recommender system model for smart urban environment

Recommender systems, deployed on the web and in mobile devices, help users in finding services and products that are addressing their needs, based on their profile. On the other hand, such systems help also organizations in promoting their products or services to a targeted market. Users in mobility in smart urban spaces are surrounded with products and services, such as mobile device applications. In this paper, we are presenting the result of a survey, where participants had to give their opinions on recommendation modalities in several scenarios of context-aware service recommendation in urban environments. These results are followed by an analysis and a discussion.