The effective analysis and understanding of huge amount of mobility data have been a hot research topic in the last few years. In this paper, we introduce Mob-Warehouse, a Trajectory Data Warehouse which goes a step further to the state of the art on mobility analysis since it models trajectories enriched with semantics. The unit of movement is the (spatio-temporal) point endowed with several semantic dimensions including the activity, the transportation means and the mobility pat- terns. This model allows us to answer the classical Why, Who, When, Where, What, How questions providing an aggregated view of different aspects of the user movements, no longer limited to space and time. We briefly present an experiment of Mob-Warehouse on a real dataset.

The effective analysis and understanding of huge amount of mobility data have been a hot research topic in the last few years. In this paper, we introduce Mob-Warehouse, a Trajectory Data Warehouse which goes a step further to the state of the art on mobility analysis since it models trajectories enriched with semantics. The unit of movement is the (spatio-temporal) point endowed with several semantic dimensions including the activity, the transportation means and the mobility patterns. This model allows us to answer the classical Why, Who, When, Where, What, How questions providing an aggregated view of different aspects of the user movements, no longer limited to space and time. We briefly present an experiment of Mob-Warehouse on a real dataset.

Mob-Warehouse: A semantic approach for mobility analysis with a Trajectory Data Warehouse

RAFFAETA', Alessandra;RONCATO, Alessandro;
2014-01-01

Abstract

The effective analysis and understanding of huge amount of mobility data have been a hot research topic in the last few years. In this paper, we introduce Mob-Warehouse, a Trajectory Data Warehouse which goes a step further to the state of the art on mobility analysis since it models trajectories enriched with semantics. The unit of movement is the (spatio-temporal) point endowed with several semantic dimensions including the activity, the transportation means and the mobility pat- terns. This model allows us to answer the classical Why, Who, When, Where, What, How questions providing an aggregated view of different aspects of the user movements, no longer limited to space and time. We briefly present an experiment of Mob-Warehouse on a real dataset.
Advances in Conceptual Modeling - ER 2013 Workshops
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/39044
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