Mobile Phone Data for Mapping Urban Dynamics

During the last few years, new tools for estimating people’s density in cities have emerged through mobile network data. As opposed to the more traditional methods of urban surveys, the use of aggregated and anonymous mobile phone network log files has shown promise for large-scale surveys with notably smaller efforts and costs. Moreover, a frequent data feed from the mobile network has been argued to demonstrate fine grain over-time variation in urban movements, lacking from the traditional prediction methods. Despite the positivist approach to the new methodology, additional evidence is needed to show how mobile network data correlate with the actual presence of people, and how they can be used to map different urban domains. We try to address this shortcoming presenting the results of a research carried out in Lombardy Region, using mobile phone data provided by Telecom Italia, as a promising approach to assist the traditional database and analysis of urban dynamics as new challenges for urban plannin

A generalized graph-spectral approach to melodic modeling and retrieval

The development of both musicologically based and efficient music information retrieval metrics to query large music database is crucial in modern music information retrieval, knowledge management and database research. Graph spectral representation of pitch class sequences has proved to outperform other pitch class based melodic similarity methods. Here we compare different spectral approaches to structural queries in databases of symbolic music, which exploits mathematical music theory results to improve the descriptive power of representative graphs. In particular, we explore graph representation of other relevant music features like intervals. The experiments have been conducted on a subset of the RISM collection, and results have been evaluated against a ground truth for the same collection developed for the MIREX competition

Monitoring tourists and visitors through coarse mobile phone data

Visitors and tourists are among the more important urban populations for their impact on local economy, on global fluxes dimensions and on urban vitality and attractiveness. In recent years we assisted at an extraordinary increase in mobile communications and mobile phone is the widest adopted technology. Within the field of urban computing, a new approach has emerged for mapping urban dynamics. In this paper we will introduce and exploit a novel kind of data, namely HLR MSC counters. In this paper we present our research showing how this kind of data can help monitoring and mapping spatial and temporal variability of population, visitors and tourists, in the Lombardia region