| Summary: | The explosion of personal positioning devices like GPS-enabled smartphones has enabled the collection and storage of a huge amount of positioning data in the form of trajectories. Thereby, trajectory data have brought many research challenges in the process of recovery, storage and knowledge discovery in mobility as well as new applications to support our society in mobility terms.
Other research area that has been receiving great attention nowadays is the area of complex network or science of networks. Complex network is the first approach to model complex system that are present in the real world, such as economic markets, the Internet, World Wide Web and disease spreading to name a few. It has been applied in different field, like Computer Science, Biology and Physics. Therefore, complex networks have demonstrated a great potential to investigate the behavior of complex systems through their entities and the relationships that exist among them.
The present dissertation, therefore, aims at exploiting approaches to analyze mobility data using a perspective of complex networks. The first exploited approach stands for the trajectories as the main entities of the networks connecting each other through a similarity function. The second, in turn, focuses on points of interest that are visited by people, which perform some activities in these points. In addition, this dissertation also exploits the proposed methodologies in order to develop a software tool to support users in mobility analysis using complex network techniques.
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