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Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data
[article]
2019
arXiv
pre-print
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Our important findings include the identification of 90 common propagation patterns of traffic and weather entities (e.g., rain --> accident --> congestion), which results in identification of four categories ...
Pattern discovery in geo-spatiotemporal data (such as traffic and weather data) is about finding patterns of collocation, co-occurrence, cascading, or cause and effect between geospatial entities. ...
Identifying propagation patterns requires the exploration of partially ordered sets of geospatial entities, that are spatially co-located and temporally co-occurring, with potential "cause and effect" ...
arXiv:1902.06792v1
fatcat:vryzyx6oznfr5ongg4eljeqqoe
Data Mining-based DNS Log Analysis
2014
Annals of Data Science
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Data mining based approaches are able to find various patterns in the massive dynamic query traffic data. The patterns may assist the DNS service providers to detect anomalies in real time. ...
Consistent episode mining method is proposed to find how the query traffic 'propagate' at different time between different domain names. Experiments are performed on a real-word DNS log data ...
Acknowledgments Project is supported by National Natural Foundation of China #61202312/70921061 and China Internet Network Information Center. ...
doi:10.1007/s40745-014-0023-7
fatcat:tn6i2tp3gfdcziftaii6lwpteu
Mining Actionable Patterns of Road Mobility From Heterogeneous Traffic Data Using Biclustering
2021
IEEE transactions on intelligent transportation systems (Print)
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In the context of our work, a road traffic pattern is a recurrent congestion profile (w.r.t. speed limits, jam extent and flow) that can span multiple locations and time periods within a day. ...
congestion patterns robust to the inherent traffic variability and unexpected occurrence of events, taking also into consideration the varying degrees of congestion severity; and iv) the need to guarantee ...
[51] proposed an extension of a classic pattern mining algorithm-FP-Growth-to mine patterns of daily congested traffic based on traffic sensor data, and build a representation of congestion propagation ...
doi:10.1109/tits.2021.3057240
fatcat:zgn5pjhsk5c4tn6wpa2rdwga2i
Revealing Recurrent Urban Congestion Evolution Patterns with Taxi Trajectories
2018
ISPRS International Journal of Geo-Information
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Therefore, we investigated recurrent congestion patterns by mining historical taxi trajectory data that were collected in Harbin, China. ...
Mining urban recurrent congestion evolution patterns can assist with congestion cause analysis and the creation of alleviating strategies. ...
, discovering the RC area, and measuring the RC evolution patterns. ...
doi:10.3390/ijgi7040128
fatcat:bozkvihq2jfbzgoiegnpwqvwxu
Towards a taxonomy of movement patterns
2008
Information Visualization
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A review of research that has been carried out on data mining and visual analysis of movement patterns suggests that there is little agreement on the relevant types of movement patterns and only few, isolated ...
This paper intends to contribute to the development of a toolbox of data mining algorithms and visual analytic techniques for movement analysis by developing firstly a conceptual framework for movement ...
Propagation: Propagation occurs when one object starts to show a certain movement parameter value, and little by little other objects start adopting the same pattern. ...
doi:10.1057/palgrave.ivs.9500182
fatcat:w2gmznvuzbcnnaxdmmbcmamsla
Predicting Traffic Flow Propagation Based on Congestion at Neighbouring Roads Using Hidden Markov Model
2021
IEEE Access
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Generally, traffic congestion is a ripple effect of a road congestion on neighboring roads. When congestion occurs, it will propagate through the road network due to increasing traffic flow. ...
One of the complexities of traffic congestion is unpredictability, thus it is difficult to represent traffic flows by numerical equations. ...
There are several studies involved in predicting propagation of traffic congestion. Studies by [13] [14] [15] , used graph approach to estimate congestion propagation. ...
doi:10.1109/access.2021.3075911
fatcat:j3qxyft6pnccbns6l2qohrylmu
A Survey on Urban Traffic Anomalies Detection Algorithms
2019
IEEE Access
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The first category groups solutions that detect flow outliers and includes statistical, similarity and pattern mining approaches. ...
INDEX TERMS Urban traffic analysis, outlier detection, machine learning, data mining. ...
The discovered patterns are then used to find anomalies such causal interaction, congested patterns, hot spot detection, and so on. ...
doi:10.1109/access.2019.2893124
fatcat:23kz4jxg3be6hojt6s2uy2hu4i
Traffic mining in a road-network: How does the traffic flow?
2008
International Journal of Business Intelligence and Data Mining
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We exploit this graph in order to analyse the traffic flow in the network and to discover traffic relationships like propagation, split and merge of traffic among the road segments. ...
Ntoutsi is supported by the Heracletos program co-funded by the European Union-European Social Fund and National Resources-EPEAEK II). G. ...
Acknowledgements This work is partially supported by FP6/IST Programme of the European Union under the GeoPKDD project (2005)(2006)(2007)(2008). I. ...
doi:10.1504/ijbidm.2008.017977
fatcat:z3ygte4bk5e7rcwbk3uovw4nru
Spatiotemporal Data Mining: A Survey on Challenges and Open Problems
[article]
2021
arXiv
pre-print
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Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay between space and time. ...
We explain issues related to STDM tasks of classification, clustering, hotspot detection, association and pattern mining, outlier detection, visualisation, visual analytics, and computer vision tasks. ...
bird migration [324] , and frequent pattern mining to discover the sequence of visited locations and the transition times between them [95]. ...
arXiv:2103.17128v1
fatcat:ci5pt5bytndr5inolznjsaizpi
Mining Topological Dependencies of Recurrent Congestion in Road Networks
2021
ISPRS International Journal of Geo-Information
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The discovery of spatio-temporal dependencies within urban road networks that cause Recurrent Congestion (RC) patterns is crucial for numerous real-world applications, including urban planning and the ...
This article proposes the ST-Discovery algorithm, a novel unsupervised spatio-temporal data mining algorithm that facilitates effective data-driven discovery of RC dependencies induced by the road network ...
If the city centre is congested, the congestion is likely to propagate to the subgraphs as well. ...
doi:10.3390/ijgi10040248
fatcat:2fnygc6zffdypo2w5674k5rzny
A Bio-chemical Approach to Awareness in Pervasive Systems
2013
Proceedings of First International Workshop on Sensing and Big Data Mining - SENSEMINE'13
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Here, applications are challenged to become aware of their surroundings: to discover, filter and reason on information relevant to their goals. ...
Acknowledgments This work is supported by the Self-Aware Pervasive Service Ecosystems project (EU FP7-FET, Contract No. 256873). ...
segmentation) to the discovered patterns by choosing the pattern most similar to the live sensor trace. ...
doi:10.1145/2536714.2536721
dblp:conf/sensys/StevensonYDCRZ13
fatcat:3hmijdsl6jccnjpzcsukqdg3vy
Visual Exploration of Sparse Traffic Trajectory Data
2014
IEEE Transactions on Visualization and Computer Graphics
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We apply existing trajectory aggregation techniques to the dataset, studying cell status pattern and inter-cell flow pattern. ...
It allows us to check how traffic congestion on one cell is correlated with traffic flows on neighbouring links, and with route selection in its neighbourhood. ...
This work is supported by NSFC No. 61170204 and HKUST grant No. SRFI11EG15PG. This work is also partially supported by NSFC Key Project No. 61232012. ...
doi:10.1109/tvcg.2014.2346746
pmid:26356895
fatcat:dj24unsng5a2xjoiwsbujfkqgm
From Twitter to Traffic Predictor: Next-Day Morning Traffic Prediction Using Social Media Data
[article]
2020
arXiv
pre-print
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In this paper, we propose to mine Twitter messages as a probing method to understand the impacts of people's work and rest patterns in the evening/midnight of the previous day to the next-day morning traffic ...
We make use of such relationships to build a predictive framework which forecasts morning commute congestion using people's tweeting profiles extracted by 5 am or as late as the midnight prior to the morning ...
Center for mobility 795 sponsored by the U.S. ...
arXiv:2009.13794v1
fatcat:l52fq6iqbfaqnnjzn7a4rxuscq
A survey on next location prediction techniques, applications, and challenges
2022
EURASIP Journal on Wireless Communications and Networking
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It is challenging to analyze and mine trajectory data due to the complex characteristics reflected in human mobility, which is affected by multiple contextual information. ...
In next location prediction, trajectory is represented by a sequence of timestamped geographical locations. ...
The second challenge we notice is how to discover knowledge to understand different human mobility behaviors, which needs investigation of pattern mining algorithms in trajectory mining. ...
doi:10.1186/s13638-022-02114-6
fatcat:s2ixs3ftibaobighbik6ikgfce
Urban Sensing Using Mobile Phone Network Data: A Survey of Research
2014
ACM Computing Surveys
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In Wu et al., 2008) authors discovered that people calling while connected to the same cell tower (co-location) are a good proxy for face-to-face meetings. ...
phone network data has been mined also to integrate calling and location pattern in order to help inferring face-to-face meetings. ...
doi:10.1145/2655691
fatcat:bctetyuz5rdehln4uieeb5nbf4
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