A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility prediction
Prediction of individual mobility is crucial in human mobility related applications. Whereas,
existing research on individual mobility prediction mainly focuses on next location prediction …
existing research on individual mobility prediction mainly focuses on next location prediction …
Context-aware deep model for joint mobility and time prediction
Mobility prediction, which is to predict where a user will arrive based on the user's historical
mobility records, has attracted much attention. We argue that it is more useful to know not …
mobility records, has attracted much attention. We argue that it is more useful to know not …
[PDF][PDF] HST-LSTM: A hierarchical spatial-temporal long-short term memory network for location prediction.
The widely use of positioning technology has made mining the movements of people
feasible and plenty of trajectory data have been accumulated. How to efficiently leverage …
feasible and plenty of trajectory data have been accumulated. How to efficiently leverage …
Deepmove: Predicting human mobility with attentional recurrent networks
Human mobility prediction is of great importance for a wide spectrum of location-based
applications. However, predicting mobility is not trivial because of three challenges: 1) the …
applications. However, predicting mobility is not trivial because of three challenges: 1) the …
Predicting human mobility via graph convolutional dual-attentive networks
Human mobility prediction is of great importance for various applications such as smart
transportation and personalized recommender systems. Although many traditional pattern …
transportation and personalized recommender systems. Although many traditional pattern …
Predicting human mobility via variational attention
An important task in Location based Social Network applications is to predict mobility-
specifically, user's next point-of-interest (POI)-challenging due to the implicit feedback of …
specifically, user's next point-of-interest (POI)-challenging due to the implicit feedback of …
Exploring trajectory prediction through machine learning methods
Human mobility prediction is of great importance in a wide range of modern applications in
different fields such as personalized recommendation systems, the fifth-generation (5G) …
different fields such as personalized recommendation systems, the fifth-generation (5G) …
A hybrid Markov-based model for human mobility prediction
Human mobility behavior is far from random, and its indicators follow non-Gaussian
distributions. Predicting human mobility has the potential to enhance location-based …
distributions. Predicting human mobility has the potential to enhance location-based …
A spatial-temporal-semantic neural network algorithm for location prediction on moving objects
F Wu, K Fu, Y Wang, Z Xiao, X Fu - Algorithms, 2017 - mdpi.com
Location prediction has attracted much attention due to its important role in many location-
based services, such as food delivery, taxi-service, real-time bus system, and advertisement …
based services, such as food delivery, taxi-service, real-time bus system, and advertisement …
MobTCast: Leveraging auxiliary trajectory forecasting for human mobility prediction
Human mobility prediction is a core functionality in many location-based services and
applications. However, due to the sparsity of mobility data, it is not an easy task to predict …
applications. However, due to the sparsity of mobility data, it is not an easy task to predict …