Currently, mobility data is revolutionizing the traditional fields of spatio-temporal reasoning and decision making analysis, not only to scale-up to the large and growing data volumes, but also to address complex questions related to change, trends, duration, and evolution. In mobility data, space and time are inextricably linked, since humans, robots and systems that dynamically act, and interact within social networks, are embedded in space, and any change is often the result of actions and events. Actions and events are a critical link to the external world, in a predictive as well as an explanatory sense: our anticipations of spatial reality conform to our domain knowledge of the effects of actions and events in the real world (i.e. inductive reasoning). Similarly, explanations of the perceived reality also are established on the basis of such a priori domain notions (i.e. deductive reasoning).
Spatio-temporal reasoning and decision support tools
Renso C;
2014
Abstract
Currently, mobility data is revolutionizing the traditional fields of spatio-temporal reasoning and decision making analysis, not only to scale-up to the large and growing data volumes, but also to address complex questions related to change, trends, duration, and evolution. In mobility data, space and time are inextricably linked, since humans, robots and systems that dynamically act, and interact within social networks, are embedded in space, and any change is often the result of actions and events. Actions and events are a critical link to the external world, in a predictive as well as an explanatory sense: our anticipations of spatial reality conform to our domain knowledge of the effects of actions and events in the real world (i.e. inductive reasoning). Similarly, explanations of the perceived reality also are established on the basis of such a priori domain notions (i.e. deductive reasoning).| File | Dimensione | Formato | |
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Descrizione: Spatio-temporal reasoning and decision support tools
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