Context-Awareness in Location Based Services in the Big Data Era

Integrating contextual information into the process of location-based service delivering is an emerging trend towards more advanced techniques aiming at personalization and intelligence of location-based services in the big data era. This chapter provides a systematic review of current context-aware location-based service systems using big data by analysing the methodological and practical choices that their developers made during the main phases of the context awareness process (i.e. context acquisition, context representation, and context reasoning and adaptation). Specifically, the chapter analyses ten location-based services, developed over the five years 2010-2014, by focusing on (1) context categories, data sources and level of automation of the context acquisition, (2) context models applied for context representation, and (3) adaptation strategies and reasoning methodologies used for context reasoning and adaptation. For each of these steps, a set of research questions and evaluation criteria are extracted that we use to evaluate and compare the surveyed context-aware location-based services. The results of this comparison are used to outline challenges and opportunities for future research in this research field.