Exploring the Design Space of Context-aware Recommender Systems that Suggest Mobile Applications

Abstract

Current technology development in mobile computing and upcoming application stores enable an easy development and distribution of mobile applications. This leads to an increasing number of available applications and to the user’s problem of content discovery. Recommender systems aim at guiding users to relevant items. Currently, recommender systems that suggest mobile applications neglect that the usage of mobile devices is characterized by perpetual changes of a user’s context. In this paper, we give rise to the contextaware recommendation of mobile applications. We explore the design space of recommender systems for mobile applications and describe the different dimensions and techniques for capturing the users, the items, the contexts and the corresponding relevances. For proof of concept we present the prototype of a recommender system that combines the design options in a hitherto unexplored way.