Nowadays heterogeneous mobile data sources are producing an enor- mous amount of contextual information that can improve our interpreta- tion of discovered mobility patterns. Because both an entity and the data sources can be mobile, what context is and how it can be used to inter- pret mobility patters may vary anyplace at anytime. This paper describes an approach for tailoring mobility patterns based on the synergy of trajec- tory and mobility pattern annotation techniques, where contexts are rep- resented as dynamic semantic views. These views are obtained after the classification of context variables that are selected based on the classifica- tion criteria previously proposed for a taxonomy of collective phenom- ena. An experiment is used to illustrate the proposed approach for tailor- ing moving flock patterns to contexts of visitors in a recreational area.
Tailoring trajectories and their moving patterns to contexts
Renso C
2013
Abstract
Nowadays heterogeneous mobile data sources are producing an enor- mous amount of contextual information that can improve our interpreta- tion of discovered mobility patterns. Because both an entity and the data sources can be mobile, what context is and how it can be used to inter- pret mobility patters may vary anyplace at anytime. This paper describes an approach for tailoring mobility patterns based on the synergy of trajec- tory and mobility pattern annotation techniques, where contexts are rep- resented as dynamic semantic views. These views are obtained after the classification of context variables that are selected based on the classifica- tion criteria previously proposed for a taxonomy of collective phenom- ena. An experiment is used to illustrate the proposed approach for tailor- ing moving flock patterns to contexts of visitors in a recreational area.| File | Dimensione | Formato | |
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Descrizione: Tailoring Trajectories and their Moving Patterns to Contexts
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