  In the last decade, digital footprints have been used to cluster population
activity into functional areas of cities.
  However, a key aspect has been overlooked: we experience our cities not only
by performing activities at specific destinations, but also by moving from one
place to another.
  In this paper, we propose to analyze and cluster the city based on how people
move through it. Particularly, we introduce Mobilicities, automatically
generated travel patterns inferred from mobile phone network data using NMF, a
matrix factorization model.
  We evaluate our method in a large city and we find that mobilicities reveal
latent but at the same time interpretable mobility structures of the city. Our
results provide evidence on how clustering and visualization of aggregated
phone logs could be used in planning systems to interactively analyze city
structure and population activity.
