  Smartphones and portable devices have become ubiquitous and part of
everyone's life. Due to the fact of its portability, these devices are perfect
to record individuals' traces and life-logging generating vast amounts of data
at low costs. These data is emerging as a new source for studies in human
mobility patterns raising the number of research projects and techniques aiming
to analyze and retrieve useful information from it. The aim of this paper is to
explore GPS raw data from different individuals in a community and apply data
mining algorithms to identify meaningful places in a region and describe user's
profiles and its similarities. We evaluate the proposed method with a
real-world dataset. The experimental results show that the steps performed to
identify points of interest (POIs) and further the similarity between the users
are quite satisfactory serving as a supplement for urban planning and social
networks.
