In trajectory classification tasks, the challenge is to find the subtrajectories or a set of
features that better discriminate the class. However, there is a lack of robustness in existing …

This article comprehensively surveys the development of trajectory data classification.
Considering the critical role of trajectory data classification in modern intelligent systems for …

Trajectory classification, ie, model construction for predicting the class labels of moving
objects based on their trajectories and other features, has many important, real-world …

Several methods for trajectory classification build models exploring trajectory global
features, such as the average and the standard deviation of speed and acceleration, but for …

The ubiquity of GPS-enabled smartphones and automotive navigation systems connected to
the Internet allows us to monitor, collect, and analyze large trajectory data streams in real …

Nowadays, the increasing number of moving objects tracking sensors, results in the
continuous flow of high-frequency and high-volume data streams. This phenomenon can …

Trajectory classification has many useful applications. Existing works on trajectory
classification do not consider the duration information of trajectory. In this paper, we extract …

In the last few years trajectory classification has been applied to many real problems,
basically considering the dimensions of space and time or attributes inferred from these …

Trajectory classification techniques face various challenges due to varying length and lack
of the presence of clear boundaries among the trajectory classes. To overcome such …

The advances in location-acquisition and mobile computing techniques have generated
massive spatial trajectory data, which represent the mobility of a diversity of moving objects …