How can knowing the location of my friends be used to more accurately predict my location? This paper ex-plores socially-aware location prediction under a partic-ularly challenging setting where the underlying interac-tions and social network are unknown and must be in-ferred over continuous spatiotemporal data. Our method samples inferred network topology using a linear re-gression model to predict future individual locations. We present an in-depth empirical study comparing dif-ferent network models and network sampling regimes under a bootstrapped sampling baseline. Furthermore, our qualitative analysis demonstrates the value of social information in population mobility modeling under our application’s challenges
Understanding and predicting human mobility is a crucial component of transportation planning and ma...
Location data is a powerful source of information to discover user’s trends and routines. A suitable...
With the popularity of location-based social networks, location prediction has become an important t...
Abstract Location-based social networks (LBSNs) have attracted an increas-ing number of users in rec...
Humans are social animals and they interact with differ-ent communities of friends to conduct differ...
As there is great differences of movement patterns and social correlation between weekdays and weeke...
Humans are social animals, they interact with different com-munities of friends to conduct different...
Planning and operations in urban spaces are strongly affected by human mobility behavior. A better u...
As a bridge between social media and physical space, location information will potentially make the ...
Geolocated social media data provides a powerful source of information about place and regional huma...
Social networks are becoming one of the most popular forms of communication between individuals worl...
We propose a novel network-based approach for location estimation in social media that integrates ev...
The emergence of location-based social networks provides an unprecedented chance to study the intera...
In recent years, researchers have sought to capture the daily life location behaviour of groups of p...
Abstract—Location-Based services with social networks im-prove users ’ experience and enrich people’...
Understanding and predicting human mobility is a crucial component of transportation planning and ma...
Location data is a powerful source of information to discover user’s trends and routines. A suitable...
With the popularity of location-based social networks, location prediction has become an important t...
Abstract Location-based social networks (LBSNs) have attracted an increas-ing number of users in rec...
Humans are social animals and they interact with differ-ent communities of friends to conduct differ...
As there is great differences of movement patterns and social correlation between weekdays and weeke...
Humans are social animals, they interact with different com-munities of friends to conduct different...
Planning and operations in urban spaces are strongly affected by human mobility behavior. A better u...
As a bridge between social media and physical space, location information will potentially make the ...
Geolocated social media data provides a powerful source of information about place and regional huma...
Social networks are becoming one of the most popular forms of communication between individuals worl...
We propose a novel network-based approach for location estimation in social media that integrates ev...
The emergence of location-based social networks provides an unprecedented chance to study the intera...
In recent years, researchers have sought to capture the daily life location behaviour of groups of p...
Abstract—Location-Based services with social networks im-prove users ’ experience and enrich people’...
Understanding and predicting human mobility is a crucial component of transportation planning and ma...
Location data is a powerful source of information to discover user’s trends and routines. A suitable...
With the popularity of location-based social networks, location prediction has become an important t...