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Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data [article]

Sobhan Moosavi, Mohammad Hossein Samavatian, Arnab Nandi, Srinivasan Parthasarathy, Rajiv Ramnath
2019 arXiv   pre-print
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

Hongyuan Cui, Jiajun Yang, Ying Liu, Zheng Zheng, Kaichao Wu
2014 Annals of Data Science  
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

Francisco Neves, Anna C. Finamore, Sara C. Madeira, Rui Henriques
2021 IEEE transactions on intelligent transportation systems (Print)  
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  
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

Somayeh Dodge, Robert Weibel, Anna-Katharina Lautenschütz
2008 Information Visualization  
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

Bagus Priambodo, Azlina Ahmad, Rabiah Abdul Kadir
2021 IEEE Access  
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

Youcef Djenouri, Asma Belhadi, Jerry Chun-Wei Lin, Djamel Djenouri, Alberto Cano
2019 IEEE Access  
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?

Irene Ntoutsi, Nikos Mitsou, Gerasimos Marketos
2008 International Journal of Business Intelligence and Data Mining  
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]

Ali Hamdi, Khaled Shaban, Abdelkarim Erradi, Amr Mohamed, Shakila Khan Rumi, Flora Salim
2021 arXiv   pre-print
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

Nicolas Tempelmeier, Udo Feuerhake, Oskar Wage, Elena Demidova
2021 ISPRS International Journal of Geo-Information  
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

Graeme Stevenson, Juan Ye, Simon Dobson, Gabriella Castelli, Alberto Rosi, Franco Zambonelli
2013 Proceedings of First International Workshop on Sensing and Big Data Mining - SENSEMINE'13  
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

Zuchao Wang, Tangzhi Ye, Min Lu, Xiaoru Yuan, Huamin Qu, Jacky Yuan, Qianliang Wu
2014 IEEE Transactions on Visualization and Computer Graphics  
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]

Weiran Yao, Sean Qian
2020 arXiv   pre-print
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

Ayele Gobezie Chekol, Marta Sintayehu Fufa
2022 EURASIP Journal on Wireless Communications and Networking  
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

Francesco Calabrese, Laura Ferrari, Vincent D. Blondel
2014 ACM Computing Surveys  
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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