Results 251 to 260 of about 76,600 (295)

Multi-granularity Visualization of Trajectory Clusters Using Sub-trajectory Clustering

2009 IEEE International Conference on Data Mining Workshops, 2009
With the surging of the requirements of location-based services, mining various interesting patterns from the spatial data becomes more and more important. In this paper, we propose an approach for visualizing the trajectory clustering results based on sub-trajectory clusters discovered from large-scale trajectory data.
Cheng Chang, Baoyao Zhou
openaire   +1 more source

Online clustering of streaming trajectories

Frontiers of Computer Science, 2018
With the increasing availability of modern mobile devices and location acquisition technologies, massive trajectory data of moving objects are collected continuously in a streaming manner. Clustering streaming trajectories facilitates finding the representative paths or common moving trends shared by different objects in real time. Although data stream
Jiali Mao, Qiuge Song, Cheqing Jin, Zhigang Zhang, Aoying Zhou   +4 more
openaire   +1 more source

Label-Based Trajectory Clustering in Complex Road Networks

IEEE Transactions on Intelligent Transportation Systems, 2020
In the data mining of road networks, trajectory clustering of moving objects is of particular interest for its practical importance in many applications.
Xinzheng Niu, Ting Chen, Chase Q Wu
exaly   +2 more sources

Trajectory kinematics descriptor for trajectory clustering in surveillance videos

2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015
Trajectories provide spatial-temporal information of foreground objects for event clustering and analysis. Because of the kinematic properties of foreground objects, the lengths of trajectories will be different which lead to the length problem of assessing similarity between two or more trajectories. To solve the problem, we propose a novel descriptor
Wei-Cheng Wang, Pau-Choo Chung, Hsin-Wei Cheng, Chun-Rong Huang   +3 more
openaire   +1 more source

Fast large-scale trajectory clustering

Proceedings of the VLDB Endowment, 2019
In this paper, we study the problem of large-scale trajectory data clustering,k-paths, which aims to efficiently identifyk"representative" paths in a road network. Unlike traditional clustering approaches that require multiple data-dependent hyperparameters,k-paths can be used for visual exploration in applications such as traffic monitoring, public ...
Sheng Wang 0007, Zhifeng Bao, J. Shane Culpepper, Timos Sellis, Xiaolin Qin   +4 more
openaire   +3 more sources

A Complete Framework for Clustering Trajectories

2009 21st IEEE International Conference on Tools with Artificial Intelligence, 2009
The increasing availability of huge amounts of thin data, i.e. data pertaining to time and positions generated by different sources with a wide variety of technologies (e.g., RFID tags, GPS, GSM networks) leads to large spatio-temporal data collections. Mining such amounts of data is challenging, since the possibility to extract useful information from
openaire   +4 more sources

Non-separable Transforms for Clustering Trajectories

2011
Trajectory data refer to time and position of moving objects generated by different sources using a wide variety of technologies (e.g., RFID tags, GPS, GSM networks). Mining such amounts of data is challenging, since the possibility to extract useful information from these peculiar kind of data is crucial in many application scenarios such as vehicle ...
Alfredo Cuzzocrea, Elio Masciari
openaire   +6 more sources

Trajectory clustering in road network environment

2009 IEEE Symposium on Computational Intelligence and Data Mining, 2009
This paper proposes a new trajectory clustering scheme for objects moving on road networks. A trajectory on road networks can be defined as a sequence of road segments a moving object has passed by. We first propose a similarity measurement scheme that judges the degree of similarity by considering the total length of matched road segments.
Jung-Im Won, Sang-Wook Kim, Ji-Haeng Baek, Junghoon Lee   +3 more
openaire   +1 more source

Hierarchical trajectory clustering for spatio-temporal periodic pattern mining

Expert Systems With Applications, 2018
Spatio-temporal periodic pattern mining is to find temporal regularities for interesting places. Many real world spatio-temporal phenomena present sequential and hierarchical nature.
Kyungmi Lee, Ickjai Lee
exaly   +2 more sources

A Framework for Trajectory Clustering

2009
The increasing availability of huge amounts of "thin" data, i.e. data pertaining to time and positions generated by different sources with a wide variety of technologies (e.g., RFID tags, GPS, GSM networks) leads to large spatio-temporal data collections. Mining such amounts of data is challenging, since the possibility of extracting useful information
openaire   +4 more sources