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Behavioral patterns can be extracted from the traces of past human activities through a semantic- enriched knowledge discovery process. Here, positioning data are first transformed in semantically enriched trajectory data stored in a database. Then, mobility patterns, the most common movements emerging from data, are computed with data mining algorithms. A further semantic enrichment step is needed to give context-dependent meaning to the discovered patterns. New challenging research topics result from this work. Among them, we believe that studying mobility form a complex network point of view may offer a complementary approach to the human mobility understanding in such complex form of data. Several application domain may benefit from the results of this research, as mobility management institutions.
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Start Date
1 July 2012
End Date
30 June 2014
Istituto di Scienza e Tecnologie dell’Informazione, National Research Council of Italy (ISTI-CNR)