A BiLSTM-CNN model for predicting users' next locations based on geotagged social media
Location prediction based on spatio-temporal footprints in social media is instrumental to
various applications, such as travel behavior studies, crowd detection, traffic control, and …
various applications, such as travel behavior studies, crowd detection, traffic control, and …
A tensor decomposition based collaborative filtering algorithm for time-aware POI recommendation in LBSN
M Yin, Y Liu, X Zhou, G Sun - Multimedia Tools and Applications, 2021 - Springer
Point of interest (POI) recommendation problem in location based social network (LBSN) is
of great importance and the challenge lies in the data sparsity, implicit user feedback and …
of great importance and the challenge lies in the data sparsity, implicit user feedback and …
Strategic and crowd-aware itinerary recommendation
There is a rapidly growing demand for itinerary planning in tourism but this task remains
complex and difficult, especially when considering the need to optimize for queuing time and …
complex and difficult, especially when considering the need to optimize for queuing time and …
Privacy for 5G-supported vehicular networks
Vehicular networks allow billions of vehicular users to be connected to report and exchange
real-time data for offering various services, such as navigation, ride-hailing, smart parking …
real-time data for offering various services, such as navigation, ride-hailing, smart parking …
Trust-aware Location Recommendation in Location-based Social Networks
D Cantürk - 2021 - open.metu.edu.tr
Users can share their location with other social network users through location-embedded
information in LBSNs (Location-Based Social Network). LBSNs contain useful resources …
information in LBSNs (Location-Based Social Network). LBSNs contain useful resources …