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Learning deep representation for trajectory clustering
Expert Systems, 2018AbstractTrajectory 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 higher level applications such as location prediction and activity recognition.
Di Yao 0001 +6 more
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Clustering and aggregating clues of trajectories for mining trajectory patterns and routes
The VLDB Journal, 2011In this paper, we propose a new trajectory pattern mining framework, namely Clustering and Aggregating Clues of Trajectories (CACT), for discovering trajectory routes that represent the frequent movement behaviors of a user. In addition to spatial and temporal biases, we observe that trajectories contain silent durations, i.e., the time durations when ...
Chih-Chieh Hung +2 more
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An approach for user’s trajectory prediction based on the trajectory cluster
Wuhan University Journal of Natural Sciences, 2012The existing user’s trajectory prediction methods considered little about the interrelation among users and would fail if the user historical trajectory data were lack. This paper presents a user’s trajectory prediction model and corresponding algorithms by the historical trajectories of users based on the trajectory cluster.
Ruiyuan Li +5 more
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TRUSTER: TRajectory Data Processing on ClUSTERs
2009With the continued advancements in location-based services involved infrastructures, large amount of time-based location data are quickly accumulated. Distributed processing techniques on such large trajectory data sets are urgently needed. We propose TRUSTER: a distributed trajectory data processing system on clusters.
Bin Yang 0002 +3 more
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Clustering Algorithm for Network Constraint Trajectories
2008Spatial data mining is an active topic in spatial databases. This paper proposes a new clustering method for moving object trajectories databases. It applies specifically to trajectories that only lie on a predefined network. The proposed algorithm (NETSCAN) is inspired from the well-known density based algorithms.
Ahmed Kharrat +3 more
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Exploratory Trajectory Clustering with Distance Geometry
2016We present here an example of how a large, multi-dimensional unstructured data set, namely aircraft trajectories over the United States, can be analyzed using relatively straightforward unsupervised learning techniques. We begin by adding a rough structure to the trajectory data using the notion of distance geometry.
Andrew T. Wilson +2 more
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Behavioral Segmentation and clustering of Geospatial Trajectories
2023 ML/DL Workshop - Albuquerque, New Mexico, United States of America - July - 2023, 2023Jessica L. Jones +6 more
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Ship AIS Trajectory Clustering: An HDBSCAN-Based Approach
Journal of Marine Science and Engineering, 2021Pengfei Chen +2 more
exaly
Trajectory Clustering via Effective Partitioning
2009The increasing availability of huge amounts of data pertaining to time and positions generated by different sources using a wide variety of technologies (e.g., RFID tags, GPS, GSM networks) leads to large spatial data collections. Mining such amounts of data is challenging, since the possibility to extract useful information from this peculiar kind of ...
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Maritime traffic flow clustering analysis by density based trajectory clustering with noise
Ocean Engineering, 2022Jiaxuan Yang, Yuan Liu, Chengtao Ji
exaly