Results 271 to 280 of about 50,329,501 (342)

Trajectory Data Classification

ACM Transactions on Intelligent Systems and Technology, 2019
This article comprehensively surveys the development of trajectory data classification. Considering the critical role of trajectory data classification in modern intelligent systems for surveillance security, abnormal behavior detection, crowd behavior analysis, and traffic control, trajectory data classification has attracted growing attention ...
Jiang Bian 0006, Dayong Tian, Yuanyan Tang, Dacheng Tao   +3 more
openaire   +1 more source

Trajectory Data Warehouses

2013
The previous chapter focused on the analysis of the spatial features of static objects such as stores, cities, or states, where by static we mean that the spatial features of these objects do not change (or change exceptionally) across time. However, there is a wide range of applications that require the analysis of the so-called moving objects, that ...
Vaisman, Alejandro Ariel, Zimanyi, Esteban   +1 more
openaire   +2 more sources

Private Trajectory Data Publication for Trajectory Classification

2019
Trajectory classification (TC), i.e., predicting the class labels of moving objects based on their trajectories and other features, has many important real-world applications. Private trajectory data publication is to anonymize trajectory data, which can be released to the public or third parties.
Huaijie Zhu, Xiaochun Yang 0001, Bin Wang 0015, Leixia Wang, Wang-Chien Lee   +4 more
openaire   +1 more source

Vehicle Trajectory Data Processing, Analytics, and Applications: A Survey

ACM Computing Surveys
Vehicles traveling through cities generate extensive vehicle trajectory collected by scalable sensors, providing excellent opportunities to address urban challenges such as traffic congestion and public safety.
Chenxi Liu, Zhu Xiao, Wangchen Long, Tong Li, Hong-Bo Jiang, Ke-Qin Li   +5 more
semanticscholar   +1 more source

An Empirical Study of Travel Behavior Using Private Car Trajectory Data

IEEE Transactions on Network Science and Engineering, 2021
Currently, an increasing number of private cars drive on roads and produce a massive volume of trajectory data. These data provide a new opportunity for understanding people's travel behavior.
Hong-Bo Jiang, Yu Zhang, Zhu Xiao, Ping Zhao, Arun K. Iyengar   +4 more
semanticscholar   +1 more source

Multiscale Visualization of Trajectory Data

2015 19th International Conference on Information Visualisation, 2015
This paper proposes a novel three-dimensional (3D) visualization tool for the trajectory analysis, helping users understand the trajectory data from different perspectives. The details of a single and a set trajectories are well covered in multiscale views by the four main linked windows, namely Traj View, Color Bar, Multi Property and Track Map.
Sheng Liang, Qing Xu 0002, Yuejun Guo 0001, Yang Fan   +3 more
openaire   +2 more sources

Querying Trajectory Data Warehouses

2009 First International Confernce on Advances in Databases, Knowledge, and Data Applications, 2009
With the fast development in mobile and communication technology, the need for moving object databases increases. Moving object databases constitute a major ingredient in many applications that are location sensitive. Traffic control, fleet management, m-commerce, and E-911 are among those emerging location based services (LBSs).
Hoda M. O. Mokhtar, Gihan Mahmoud
openaire   +2 more sources

Sampling Big Trajectory Data

Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, 2015
The increasing prevalence of sensors and mobile devices has led to an explosive increase of the scale of spatio-temporal data in the form of trajectories. A trajectory aggregate query, as a fundamental functionality for measuring trajectory data, aims to retrieve the statistics of trajectories passing a user-specified spatio-temporal region.
Yanhua Li, Chi-Yin Chow, Ke Deng, Mingxuan Yuan, Jia Zeng, Jia-Dong Zhang, Qiang Yang 0001, Zhi-Li Zhang   +7 more
openaire   +2 more sources

Spatial structures of tourism destinations: A trajectory data mining approach leveraging mobile big data

Annals of Tourism Research, 2020
The advancement of mobile technology provides an opportunity to obtain the real-time information of travelers, such as their spatial and temporal behaviors, during their visits to a destination. This study analyzes a large scale mobile phone dataset that
Sangwon Park, Yang Xu, Liu Jiang, Zhelin Chen, Shuyi Huang   +4 more
semanticscholar   +1 more source

Trajectory Data Pattern Mining

2014
In this paper, we study the problem of mining for frequent trajectories, which is crucial in many application scenarios, such as vehicle traffic management, hand-off in cellular networks, supply chain management. We approach this problem as that of mining for frequent sequential patterns.
Masciari E, Shi Gao, Carlo Zaniolo
openaire   +5 more sources