Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A survey on trajectory data management, analytics, and learning
Recent advances in sensor and mobile devices have enabled an unprecedented increase
in the availability and collection of urban trajectory data, thus increasing the demand for …
in the availability and collection of urban trajectory data, thus increasing the demand for …
A review of moving object trajectory clustering algorithms
G Yuan, P Sun, J Zhao, D Li, C Wang - Artificial Intelligence Review, 2017 - Springer
Clustering is an efficient way to group data into different classes on basis of the internal and
previously unknown schemes inherent of the data. With the development of the location …
previously unknown schemes inherent of the data. With the development of the location …
Deep representation learning for trajectory similarity computation
Trajectory similarity computation is fundamental functionality with many applications such as
animal migration pattern studies and vehicle trajectory mining to identify popular routes and …
animal migration pattern studies and vehicle trajectory mining to identify popular routes and …
Trajectory clustering via deep representation learning
Trajectory clustering, which aims at discovering groups of similar trajectories, has long been
considered as a corner stone task for revealing movement patterns as well as facilitating …
considered as a corner stone task for revealing movement patterns as well as facilitating …
Spatio-temporal trajectory similarity measures: A comprehensive survey and quantitative study
Spatio-temporal trajectory analytics are useful in diversified applications such as urban
planning, infrastructure development, and vehicular networks. Trajectory similarity measure …
planning, infrastructure development, and vehicular networks. Trajectory similarity measure …
Fast large-scale trajectory clustering
In this paper, we study the problem of large-scale trajectory data clustering, k-paths, which
aims to efficiently identify k" representative" paths in a road network. Unlike traditional …
aims to efficiently identify k" representative" paths in a road network. Unlike traditional …
Deep feature extraction from trajectories for transportation mode estimation
This paper addresses the problem of feature extraction for estimating users' transportation
modes from their movement trajectories. Previous studies have adopted supervised learning …
modes from their movement trajectories. Previous studies have adopted supervised learning …
iGeoRec: A personalized and efficient geographical location recommendation framework
Geographical influence has been intensively exploited for location recommendations in
location-based social networks (LBSNs) due to the fact that geographical proximity …
location-based social networks (LBSNs) due to the fact that geographical proximity …
Direction-preserving trajectory simplification
Trajectories of moving objects are collected in many applications. Raw trajectory data is
typically very large, and has to be simplified before use. In this paper, we introduce the …
typically very large, and has to be simplified before use. In this paper, we introduce the …
TICRec: A probabilistic framework to utilize temporal influence correlations for time-aware location recommendations
In location-based social networks (LBSNs), time significantly affects users' check-in
behaviors, for example, people usually visit different places at different times of weekdays …
behaviors, for example, people usually visit different places at different times of weekdays …