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

Renso C;Trasarti R
2014

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 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.
2014
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
Jeffrey Parsons, Dickson Chiu
Advances in Conceptual Modeling
127
136
978-3-319-14138-1
http://link.springer.com/chapter/10.1007%2F978-3-319-14139-8_15#page-1
Sì, ma tipo non specificato
Data warehouse
Semantic trajectories
ER 2013 Workshops, LSAWM, MoBiD, RIGiM, SeCoGIS, WISM, DaSeM, SCME, and PhD Symposium - Revised Selected Papers (Hong Kong, China, November 11-13 2013).
2
02 Contributo in Volume::02.01 Contributo in volume (Capitolo o Saggio)
268
restricted
Wagner R.; de MacEdo, José A. F.; Raffaetà A.; Roncato A.; Renso C.; Trasarti R.
info:eu-repo/semantics/bookPart
   Semantic EnrichmEnt of trajectory Knowledge discovery
   SEEK
   FP7
   295179
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/271140
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