Map-Based Interaction with a Conversational Mobile Recommender System

Recommender systems are information search and decision support tools used when there is an overwhelming set of options to consider or when the user lacks the domain-specific knowledge necessary to take autonomous decisions. They provide users with personalized recommendations adapted to their needs and preferences in a particular usage context. In this paper, we present an approach for integrating recommendation and electronic map technologies to build a map-based conversational mobile recommender system that can effectively and intuitively support users in finding their desired products and services. The results of our real-user study show that integrating map-based visualization and interaction in mobile recommender systems improves the system recommendation effectiveness and increases the user satisfaction.