Towards a Cross-Domain Context-Aware Recommender of Optimal Experiences

Abstract

Nowadays, many people suffer from depression, anxiety disorder, stress and bad emotions. Most of the times, the causes are a chaotic lifestyle, stressful jobs and activities, wrong habits and a permanent sense of uncertainty. Therefore, well-being plays an increasingly important role in people's lives, as it can help them to prevent chronic disease and long-term illnesses. However, well-being does not concern only healthy lifestyle, rather it is necessary to consider also mental health and interior happiness. In this position paper, we propose the idea of FlowMe, a cross-domain context-aware recommender system of optimal experiences, i.e. situations when people report feelings of deep enjoyment, forgetting the passage of time and external worries, and reaching an inner harmony on which their general happiness depends. In our perspective, FlowMe could be connected to different IoT devices and applications, such as social media, to collect data from the users and learn their mood, behaviour and habits, in order to suggest personalized optimal experiences when they are feeling a negative emotion. Also, the system will recognise when the user is in the flow doing a certain activity. FlowMe takes into account optimal experiences from various domains, considering users' preferences and their context.