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Smartphones and portable devices have become ubiquitous and part ofeveryone's life. Due to the fact of its portability, these devices are perfectto record individuals' traces and life-logging generating vast amounts of dataat low costs. These data is emerging as a new source for studies in humanmobility patterns raising the number of research projects and techniques aimingto analyze and retrieve useful information from it. The aim of this paper is toexplore GPS raw data from different individuals in a community and apply datamining algorithms to identify meaningful places in a region and describe user'sprofiles and its similarities. We evaluate the proposed method with areal-world dataset. The experimental results show that the steps performed toidentify points of interest (POIs) and further the similarity between the usersare quite satisfactory serving as a supplement for urban planning and socialnetworks.

Identifying Points of Interest and Similar Individuals from Raw GPS Data