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2019
Proceedings of the VLDB Endowment
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Convoy mining is an expensive task and existing sequential algorithms do not scale to real-life dataset sizes. ...
Thus, only a very small portion of the complete dataset is considered for mining convoys. ...
large datasets. ...
doi:10.14778/3329772.3329773
fatcat:kt23zoev35hs3ajlau7ti2n4h4
Effective Following Patterns Mining Scheme for the Movements of Objects
2016
International Journal of Grid and Distributed Computing
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In this paper, we review the progress of patterns mining mainly in frequent pattern, periodic pattern and following pattern. ...
and giving effective following patterns mining scheme for the movements of objects. ...
These are many algorithms for mining convoy pattern, but do not scale to real-life dataset sizes. Therefore, Faisal et al. [61] used distributed algorithm to settle this problem. ...
doi:10.14257/ijgdc.2016.9.6.19
fatcat:tikphhhgw5hgzchjrsthnx2ugq
Key Concepts of Group Pattern Discovery Algorithms from Spatio-Temporal Trajectories
2019
2019 15th International Conference on Semantics, Knowledge and Grids (SKG)
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The authors conclude with the proposal of a conceptual model of Universal, Streaming, Distributed and Parameter-light (UDSP) algorithm that addresses current challenges in this research area. ...
Furthermore, the currently available surveys and taxonomies in this research area do not focus on group pattern mining algorithms nor include the state-of-the-art models. ...
Another way of handling group pattern mining from large datasets are gridbased models such as moving flock [34] Taking into consideration the classification criteria we based on the differentiation of ...
doi:10.1109/skg49510.2019.00039
dblp:conf/skg/DluzniakJWX19
fatcat:jq4u7fyt2fcahnuc3a7twvs7ne
An analysis of ship escort and convoy operations in ice conditions
2017
Safety Science
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One aspect of ship convoy navigation in ice conditions is the distance kept between the icebreaker and the ships in the convoy, a form of the well-known ship domain concept. ...
The aim of this paper is to investigate selected operational aspects of convoy navigation in ice conditions in the Finnish waters of the Gulf of Finland, based on data of the Automatic Identification System ...
The authors also thank Hannah Ploskonka and Dannielle Lodge for their help in constructing the database of convoy operations. ...
doi:10.1016/j.ssci.2016.01.004
fatcat:s25bbbt3znhlvoblai7kl7x7we
ReCon: A Fast and Reliable Replica Retrieval Service for the Data Grid
2006
Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06)
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It is the core mechanism of the Data Grid in that it enables scalable and efficient sharing of large volumes of data. ...
Replication is the process of storing data in different locations to reduce access latency, improve data locality, and increase robustness, scalability and performance for distributed applications. ...
These applications use Grid systems as distributed data storages, where pieces of large datasets are replicated over several sites. ...
doi:10.1109/ccgrid.2006.83
dblp:conf/ccgrid/ZhouKKY06
fatcat:ucyeuw3kmvcmlcm6mqka3w4d4i
A review of quantitative methods for movement data
2013
International Journal of Geographical Information Science
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., XY coordinates) at discrete time intervals. 14 Methods for extracting useful information, for example space-time patterns, from these 15 increasingly large and detailed datasets have lagged behind the ...
The objective of this article is to provide a synthesis of the existing literature on 18 quantitative analysis of movement data while identifying those techniques that have merit 19 with novel datasets ...
of 402 spatial behavior in large movement databases. ...
doi:10.1080/13658816.2012.682578
fatcat:txsezqduzzg6hgtdvhbcfshw2a
Online Long-Term Trajectory Prediction Based on Mined Route Patterns
[chapter]
2020
Lecture Notes in Computer Science
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In this paper, we present a Big data framework for the prediction of streaming trajectory data by exploiting mined patterns of trajectories, allowing accurate long-term predictions with low latency. ...
The experimental study is based on real-world aviation and maritime datasets. ...
This research has also been co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation ...
doi:10.1007/978-3-030-38081-6_4
fatcat:6n5heoumwfguln3chpcp35uifm
Mining Massive-Scale Spatiotemporal Trajectories in Parallel: A Survey
[chapter]
2015
Lecture Notes in Computer Science
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In this paper, we present a comprehensive survey of the state-of-the-art techniques for mining massive-scale spatiotemporal trajectory data based on parallel computing platforms such as Graphics Processing ...
With the popularization of positioning devices such as GPS navigators and smart phones, large volumes of spatiotemporal trajectory data have been produced at unprecedented speed. ...
Furthermore, on two large scale realworld datasets, the GPU implementation achieved around 4x speedup on the R-Tree bulk loading task compared to the CPU parallel implementation. ...
doi:10.1007/978-3-319-25660-3_4
fatcat:qdkslwlgjzesdfnzvkbrpsgmti
Online clustering for trajectory data stream of moving objects
2013
Computer Science and Information Systems
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It is crucial to extract useful information from this peculiar kind of data in many application scenarios, such as vehicle traffic management, large-scale tracking management and video surveillance. ...
Our performance evaluation experiments conducted on a number of real and synthetic trajectory datasets illustrate the effectiveness, efficiency, and scalability of the algorithm. ...
in a large security system. ...
doi:10.2298/csis120723049y
fatcat:jmm7anxksjaq5o46vcy24oyczq
On Discovery of Traveling Companions from Streaming Trajectories
2012
2012 IEEE 28th International Conference on Data Engineering
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The advance of object tracking technologies leads to huge volumes of spatio-temporal data collected in the form of trajectory data stream. ...
The proposed methods are evaluated with extensive experiments on both real and synthetic datasets. The buddy-based method is an order of magnitude faster than baselines. ...
Since it is difficult to detect large size frequent itemsets [36] , the swarm pattern has limited applicability for datasets with large scale objects.
VIII. ...
doi:10.1109/icde.2012.33
dblp:conf/icde/TangZYHLHP12
fatcat:27wi7a2e5jhgjiz7onixiksabm
Spatiotemporal Pattern Mining: Algorithms and Applications
[chapter]
2014
Frequent Pattern Mining
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In this chapter, we provide an overview of spatiotemporal data mining methods. ...
Mining patterns from spatiotemporal data has many important applications in human mobility understanding, smart transportation, urban planning and ecological studies. ...
Finally, it will be interesting to consider human factor in the mining process and make the mining process more interactive and informative. ...
doi:10.1007/978-3-319-07821-2_12
fatcat:t6ecqptztrbntp5xtmuauqoasm
An analysis of wintertime navigational accidents in the Northern Baltic Sea
2017
Safety Science
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Correspondingly, visual data mining is selected as analysis approach, because of its utility in obtaining qualitative knowledge from data sources through a combination of visualization techniques and human ...
This paper presents an analysis of navigational shipping accidents in the Northern Baltic Sea area which occurred in the period 2007-2013. ...
Acknowledgements The research presented in this paper has been conducted in the context of the ''Strategic and Operational Risk Management for Wintertime Maritime Transportation System" (BONUS STORM-WINDS ...
doi:10.1016/j.ssci.2016.09.011
fatcat:akxbcp2mzvcddo3stsflikae7y
Spatiotemporal Data Mining: A Survey on Challenges and Open Problems
[article]
2021
arXiv
pre-print
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Several available surveys capture STDM advances and report a wealth of important progress in this field. ...
However, STDM challenges and problems are not thoroughly discussed and presented in articles of their own. ...
Consequently, real-time large-scale sensor data are captured via distributed connected objects equipped with sensors. ...
arXiv:2103.17128v1
fatcat:ci5pt5bytndr5inolznjsaizpi
Real-time distributed co-movement pattern detection on streaming trajectories
2019
Proceedings of the VLDB Endowment
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Nevertheless, in a streaming setting, unbounded data arrives in real time, making pattern detection challenging. ...
With the widespread deployment of mobile devices with positioning capabilities, increasingly massive volumes of trajectory data are being collected that capture the movements of people and vehicles. ...
In contrast, we aim to support general co-movement pattern mining, and provide a distributed framework capable of supporting real-time mining on large-scale streaming trajectories. ...
doi:10.14778/3339490.3339502
fatcat:b2dbmflixnd5zovvsxnc3es6ky
MinHash hierarchy for privacy preserving trajectory sensing and query
2017
Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks - IPSN '17
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The MinHash hierarchy has a total of near linear storage, linear construction cost, and logarithmic update cost. The cost of a popular path query is logarithmic in the number of checkpoints. ...
The checkpoints detect the appearances of mobile entities in the proximity, meanwhile, employ the MinHash signatures to record the set of mobile entities passing by. ...
CONCLUSION In this paper, we proposed a distributed sensing framework by using the MinHash hierarchy for efficient real-time query of popular paths among distributed checkpoints. ...
doi:10.1145/3055031.3055076
dblp:conf/ipsn/DingNZG17
fatcat:hinpuio5vnc67ansxh7pt35i44
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