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A review of urban computing for mobile phone traces: current methods, challenges and opportunities
In this work, we present three classes of methods to extract information from triangulated
mobile phone signals, and describe applications with different goals in spatiotemporal …
mobile phone signals, and describe applications with different goals in spatiotemporal …
Review and classification of trajectory summarisation algorithms: From compression to segmentation
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 …
Semantic trajectories: Mobility data computation and annotation
With the large-scale adoption of GPS equipped mobile sensing devices, positional data
generated by moving objects (eg, vehicles, people, animals) are being easily collected …
generated by moving objects (eg, vehicles, people, animals) are being easily collected …
Semantic annotation of mobility data using social media
Recent developments in sensors, GPS and smart phones have provided us with a large
amount of mobility data. At the same time, large-scale crowd-generated social media data …
amount of mobility data. At the same time, large-scale crowd-generated social media data …
Warped k-means: An algorithm to cluster sequentially-distributed data
Many devices generate large amounts of data that follow some sort of sequentiality, eg,
motion sensors, e-pens, eye trackers, etc. and often these data need to be compressed for …
motion sensors, e-pens, eye trackers, etc. and often these data need to be compressed for …
Semantic management of moving objects: A vision towards smart mobility
This position paper presents our vision for the semantic management of moving objects. We
argue that exploiting semantic techniques in mobility data management can bring valuable …
argue that exploiting semantic techniques in mobility data management can bring valuable …
GRASP-UTS: an algorithm for unsupervised trajectory segmentation
An important problem in the knowledge discovery of trajectories is segmentation in subparts
(subtrajectories). Existing algorithms for trajectory segmentation generally use explicit …
(subtrajectories). Existing algorithms for trajectory segmentation generally use explicit …
SWS: an unsupervised trajectory segmentation algorithm based on change detection with interpolation kernels
Trajectory mining aims to provide fundamental insights into decision-making tasks related to
moving objects. A fundamental pre-processing step for trajectory mining is trajectory …
moving objects. A fundamental pre-processing step for trajectory mining is trajectory …
A semi-supervised approach for the semantic segmentation of trajectories
A first fundamental step in the process of analyzing movement data is trajectory
segmentation, ie, splitting trajectories into homogeneous segments based on some criteria …
segmentation, ie, splitting trajectories into homogeneous segments based on some criteria …
[PDF][PDF] A Trajectory Segmentation Algorithm Based on Interpolation-based Change Detection Strategies.
Trajectory mining is a research field which aims to provide fundamental insights into
decision-making tasks related to moving objects. One of the fundamental pre-processing …
decision-making tasks related to moving objects. One of the fundamental pre-processing …