Personalising Map Feature Content for Mobile Map Users

Abstract

Several challenges arise when displaying maps on mobile devices. Users encounter problems dealing with information overload and mapping interface interaction while on the move – issues of human-computer interaction. In addition, to effectively display maps on mobile devices, developers must address restrictions related to screen size and limited bandwidth – issues of computational efficiency. We have developed MAPPER, a novel approach for delivering personalised maps to mobile devices, which addresses mobile mapping issues from both perspectives. MAPPER generates maps containing specific spatial feature content that is tailored to the explicit preferences of users with contrasting requirements by monitoring the interactions of individuals when browsing maps. All interactions between users and maps are captured implicitly and are used to infer individual and group preferences related to specific map feature content. MAPPER provides an effective and efficient means of delivering and representing maps on mobile devices, which addresses information overload by providing exactly the map information necessary to suit user interaction preferences. In turn, tailoring map content to user preferences considerably reduces the size of vector datasets necessary to transmit and render maps. This chapter describes the map personalisation approach in MAPPER and presents a user study showing the benefits of providing a diverse set of individuals with personalised map feature content when engaged in mobile mapping tasks.