\chapter{Introduction}
{


%-------------------------------------------------------------------------
\section{The objective}
This PhD thesis deals with the study of new paradigms for exploiting data obtained from virtual and real personal digital traces (i.e. from Social Networks, Location-Based Social Networks, remote sensing and crowdsourcing, physic sensors) as a basis for the design and implementation of innovative infovis technologies, recommendation, browsing and human computer interaction systems deployed in real and virtual spaces, i.e. in online, outdoor and indoor environments. Primary objectives have been the automatic identification of functional areas within cities through the analysis of geo-located social media information and user profiling, and the detection of macro and micro events happening in urban areas. The analysis on user data and profiling have also led to research on how to exploit user profiling on SNs and human factors to improve recommendations systems on general purpose and contextual social networks but also for designing smart and personalized systems to be used in indoor locations. 
%-------------------------------------------------------------------------
\section{Contributions}
New methods for identification of functional areas in cities and for the detection of geo-localized micro and macro-events are described in Chapter~\ref{chap:urban-computing-fa}. Using these informations as a basis, personalized recommendation and routing systems as well as immersive browsing interfaces has been created that could present innovative paradigms of human computer interaction through original solutions for information visualizations. In particular it has been developed 1) a framework which exploits user profiling on social networks and data from mobile device sensors that allows the semi-automatic recommendation and assisted definition of itineraries and 2) a framework for navigating, on the web, immersive urban routes through continuous spherical images transitions which allows the fruition of multimedia materials associated to POIs. These systems exploit in part the techniques of user profiling presented in Sec. and propose and provide original solutions for information visualization. Proposed strategies of recommendation of multimedia material combined with the previously cited user profiling techniques have then been used for proposing 1) a recommender which makes an improvement to standard user and item-based recommenders implemented in a Social Network based on video annotations (the improvement has been achieved through an original exploitation of human factors, i.e.  users' self-expression in user profiles and perception of visual saliency in videos); 2) effective methods of recommendation designed for contextual SNs. New ways of recommending, browsing and navigating multimedia content in indoor real and virtual environments relying on context understanding and user localization through portable devices, ibeacon sensors, computer vision and natural interaction have been designed and implemented in real applications in original ways. Main objectives of these systems were the personalization of content and the understanding of the user context, preferences and behaviors in order to provide a more natural and targeted user experience.

}