Human Centered Big Data Analytics for Smart Applications

This thesis is concerned with Smart Applications. Smart applications are all those applications that incorporate data-driven, actionable insights in the user experience, and they allow in different contexts users to complete actions or make decisions efficiently. The differences between smart applications and traditional applications are mainly that the former are dynamic and evolve on the basis of intuition, user feedback or new data. Moreover, smart applications are data-driven and linked to the context of use. There are several aspects to be considered in the development of intelligent applications, such as machine learning algorithms for producing insights, privacy, data security and ethics. The purpose of this thesis is to study and develop human centered algorithms and systems in different contexts (retail, industry, environment and smart city) with particular attention to big data analysis and prediction techniques. The second purpose of this thesis is to study and develop techniques for the interpretation of results in order to make artificial intelligence algorithms "explainable". Finally, the third and last purpose is to develop solutions in GDPR compliant environments and then secure systems that respect user privacy.