Volunteered Geographic Information (VGI) is a process where individuals, supported by enabling technologies, behave like physical sensors to harvest georeferenced content in their surroundings. The value of this, typically heterogeneous, content has been recognized by both researchers and organizations. However, in order to be fruitfully used in various VGI-based types of application reliability and quality of particular VGI content (i.e., Points of Interest) have to be assessed. This evaluation can be based on reputation scores that summarize users' experiences with the specific content. Following this direction, our contribution provides, primarily, a new comprehensive model and a multi-layer architecture for reputation evaluation aimed to assess quality of VGI content. Secondly, we demonstrate the relevance of adopting such a framework through an applicative scenario for recommending touristic itineraries.
Reputation evaluation of georeferenced data for crowd-sensed applications
Renso C
2017
Abstract
Volunteered Geographic Information (VGI) is a process where individuals, supported by enabling technologies, behave like physical sensors to harvest georeferenced content in their surroundings. The value of this, typically heterogeneous, content has been recognized by both researchers and organizations. However, in order to be fruitfully used in various VGI-based types of application reliability and quality of particular VGI content (i.e., Points of Interest) have to be assessed. This evaluation can be based on reputation scores that summarize users' experiences with the specific content. Following this direction, our contribution provides, primarily, a new comprehensive model and a multi-layer architecture for reputation evaluation aimed to assess quality of VGI content. Secondly, we demonstrate the relevance of adopting such a framework through an applicative scenario for recommending touristic itineraries.| File | Dimensione | Formato | |
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Descrizione: Reputation evaluation of georeferenced data for crowd-sensed Reputation evaluation of georeferenced data for crowd-sensed applications applications
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