• Data Mining
• Data Mining Query Language
• Spatio-Temporal analysis

The thesis addresses a topic of great importance: a framework for data mining positioning data collected by personal mobile devices.
The main contribution of this thesis is the creation of a theoretical and practical framework in order to manage the complex Knowledge discovery process on mobility data. Hence the creation of such framework leads to the integration of very different aspects of the process with their assumptions and requirements. The result is a homogeneous system which gives the possibility to exploit the power of all the components with the same flexibilities of a database such as a new way to use the ontology for an automatic reasoning on trajectory data. Furthermore two extensions are invented and developed and then integrated in the system to confirm the extensibility of it: a innovative way to reconstruct the trajectories considering the uncertainty of the path followed and a Location prediction algorithm called WhereNext.
Another important contribution of the thesis is the experimentation on a real case of study on analysis of mobility data. It has been shown the usefulness of the system for a mobility manager who is provided with a knowledge discovery framework.