  Cellphone service-providers continuously collect Call Detail Records (CDR) as
a usage log containing spatio-temporal traces of phone users. We proposed a
multi-layered hierarchical analytical model for large spatio-temporal datasets
and applied that for the progressive exploration of social features of a city,
e.g., social activities, relationships, and groups, from CDR. This approach
utilizes CDR as the preliminary input for the initial layer, and analytical
results from consecutive layers are added to the knowledge-base to be used in
the subsequent layers to explore more detailed social features. Each subsequent
layer uses the results from previous layers, facilitating the discovery of more
in-depth social features not predictable in a single-layered approach using
only raw CDR. This model starts with exploring aggregated overviews of the
social features and gradually focuses on comprehensive details of social
relationships and groups, which facilitates a novel approach for investigating
CDR datasets for the progressive exploration of social features in a
densely-populated city.
