A survey of trajectory distance measures and performance evaluation
The proliferation of trajectory data in various application domains has inspired tremendous
research efforts to analyze large-scale trajectory data from a variety of aspects. A …
research efforts to analyze large-scale trajectory data from a variety of aspects. A …
Review and classification of trajectory summarisation algorithms: From compression to segmentation
D Amigo, D Sánchez Pedroche… - … of Distributed Sensor …, 2021 - journals.sagepub.com
With the continuous development and cost reduction of positioning and tracking
technologies, a large amount of trajectories are being exploited in multiple domains for …
technologies, a large amount of trajectories are being exploited in multiple domains for …
Efficient trajectory similarity computation with contrastive learning
The ubiquity of mobile devices and the accompanying deployment of sensing technologies
have resulted in a massive amount of trajectory data. One important fundamental task is …
have resulted in a massive amount of trajectory data. One important fundamental task is …
Periodicmove: Shift-aware human mobility recovery with graph neural network
Human mobility recovery is of great importance for a wide range of location-based services.
However, recovering human mobility is not trivial because of three challenges: 1) complex …
However, recovering human mobility is not trivial because of three challenges: 1) complex …
Fast stochastic routing under time-varying uncertainty
Data are increasingly available that enable detailed capture of travel costs associated with
the movements of vehicles in road networks, notably travel time, and greenhouse gas …
the movements of vehicles in road networks, notably travel time, and greenhouse gas …
Semi-supervised clustering with deep metric learning and graph embedding
As a common technology in social network, clustering has attracted lots of research interest
due to its high performance, and many clustering methods have been presented. The most …
due to its high performance, and many clustering methods have been presented. The most …
[HTML][HTML] Incorporation of adaptive compression into a GPU parallel computing framework for analyzing large-scale vessel trajectories
Abstract Automatic Identification System (AIS) offers a wealth of vessel navigation data,
which underpins research in maritime data mining, situational awareness, and knowledge …
which underpins research in maritime data mining, situational awareness, and knowledge …
Lane change scheduling for autonomous vehicle: A prediction-and-search framework
Automation in road vehicles is an emerging technology that has developed rapidly over the
last decade. There have been many inter-disciplinary challenges posed on existing …
last decade. There have been many inter-disciplinary challenges posed on existing …
Learning to hash for trajectory similarity computation and search
Searching for similar trajectories from a database is an important way for extracting human-
understandable knowledge. However, due to the huge volume of trajectories and high …
understandable knowledge. However, due to the huge volume of trajectories and high …
S2tul: A semi-supervised framework for trajectory-user linking
Trajectory-User Linking (TUL) aiming to identify users of anonymous trajectories, has
recently received increasing attention due to its wide range of applications, such as criminal …
recently received increasing attention due to its wide range of applications, such as criminal …