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Opportunistic networks are considered as the promising network structures to implement traditional and typical infrastructure-based communication by enabling smart mobile devices in the networks to contact with each other within a fixed communication ...
Bangyuan Chen, Lingna Chen
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A Location Prediction Methods: state of art [PDF]
The rapid use of social media made location prediction is the key to research studies based on-location services like; advertising, recommendations, climatological forecast, and security system.
Tamer Mostafa +3 more
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Location, location, location: currency effects and return predictability? [PDF]
Most international financial market studies that compare across countries utilize the US dollar as the common numeraire. We explore the little studied question of the appropriate choice for the base currency and ask if currency choice can affect the final conclusion of whether predictability exists.
Steven J. Jordan +2 more
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Learning Individual Moving Preference and Social Interaction for Location Prediction
Location prediction has attracted increasing attention in diverse fields due to its wide applications, such as traffic planning and control, weather forecasting, homeland security, and travel recommendation.
Ruizhi Wu +3 more
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Location Dependency in Video Prediction [PDF]
International Conference on Artificial Neural Networks.
Niloofar Azizi +2 more
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Location prediction has attracted much attention due to its important role in many location-based services. The existing location prediction methods have large trajectory information loss and low prediction accuracy.
Yuelei Xiao, Qing Nian
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Location prediction in location-based social networks
Developments in mobile devices and wireless networks have led to the increasing popularity of location-based socialnetworks. These networks allow users to explore new places , share their location, videos and photos and make friends. They give information about the mobility of users, which can be used to improve the networks.
Baydar, Mücahit, ALBAYRAK, Songül
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Representing Spatial Data with Graph Contrastive Learning
Large-scale geospatial data pave the way for geospatial machine learning algorithms, and a good representation is related to whether the machine learning model is effective.
Lanting Fang +3 more
doaj +1 more source
CASTLE: A CONTEXT-AWARE SPATIAL-TEMPORAL LOCATION EMBEDDING PRE-TRAINING MODEL FOR NEXT LOCATION PREDICTION [PDF]
Next location prediction is helpful for service recommendation, public safety, intelligent transportation, and other location-based applications. Existing location prediction methods usually use sparse check-in trajectories and require massive historical
J. Cheng, J. Huang, X. Zhang
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