A Mobile Recommendation System Supporting Group Collaborative Decision Making

Nowadays, recommendation services that allow users to obtain the information needed in their vicinity have become very popular among users of mobile devices. In fact, these systems guide the user to choose amongst the available information, identifying and making suggestions of relevant information based on user's preferences and context information. Furthermore, this is particular important in mobile devices with small screens, where it is essential that what is shown is truly relevant for the user in order to help him/her in the decision process. Several mobile recommender systems have been proposed but there still exist open challenges. This paper proposes BomApetite a mobile system to recommend restaurants to a group, based on the preferences of all the group participants, which integrates restaurant information from well-known platforms. The recommendation strategy considers the importance the user gives to each platform. To support group decision making the system uses a method that determines the best alternatives for the group from individual preferences and provides a voting process so that the group can reach a consensus. The results of a user study assessing the usability and usefulness of the system showed that overall participants had a favorable opinion.