Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-4053
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dc.contributor.authorDanafar, Somayeh-
dc.contributor.authorPiorkowski, Michal-
dc.contributor.authorKryszczuk, Krzysztof-
dc.date.accessioned2018-11-22T15:25:57Z-
dc.date.available2018-11-22T15:25:57Z-
dc.date.issued2017-
dc.identifier.isbn978-0-9928626-7-1de_CH
dc.identifier.issn2076-1465de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/13168-
dc.description.abstractUnderstanding human mobility patterns is of great importance for planning urban and extra-urban spaces and communication infrastructures. The omnipresence of mobile telephony in today’s society opens new avenues of discovering the patterns of human mobility by means of analyzing cellular network data. Of particular interest is analyzing passively collected Network Events (NEs) due to their scalability. However, mobility pattern analysis based on network events is challenging because of the coarse granularity of NEs. In this paper, we propose network event-based Bayesian approaches for mobility pattern recognition and reconstruction, mode of transport recognition and modeling the frequent trajectories.de_CH
dc.language.isoende_CH
dc.publisherIEEEde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectMobilityde_CH
dc.subjectTrajectoryde_CH
dc.subjectPredictionde_CH
dc.subjectSmart cityde_CH
dc.subject.ddc003: Systemede_CH
dc.subject.ddc380: Verkehrde_CH
dc.titleBayesian framework for mobility pattern discovery using mobile network eventsde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
dc.identifier.doi10.21256/zhaw-4053-
dc.identifier.doi10.23919/EUSIPCO.2017.8081372de_CH
zhaw.conference.details25th European Signal Processing Conference (EUSIPCO), Kos, 28 August - 2 September 2017de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end1109de_CH
zhaw.pages.start1105de_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.publication.reviewNot specifiedde_CH
zhaw.title.proceedings2017 25th European Signal Processing Conference (EUSIPCO)de_CH
zhaw.webfeedPredictive Analyticsde_CH
Appears in collections:Publikationen Life Sciences und Facility Management

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Danafar, S., Piorkowski, M., & Kryszczuk, K. (2017). Bayesian framework for mobility pattern discovery using mobile network events [Conference paper]. 2017 25th European Signal Processing Conference (EUSIPCO), 1105–1109. https://doi.org/10.21256/zhaw-4053
Danafar, S., Piorkowski, M. and Kryszczuk, K. (2017) ‘Bayesian framework for mobility pattern discovery using mobile network events’, in 2017 25th European Signal Processing Conference (EUSIPCO). IEEE, pp. 1105–1109. Available at: https://doi.org/10.21256/zhaw-4053.
S. Danafar, M. Piorkowski, and K. Kryszczuk, “Bayesian framework for mobility pattern discovery using mobile network events,” in 2017 25th European Signal Processing Conference (EUSIPCO), 2017, pp. 1105–1109. doi: 10.21256/zhaw-4053.
DANAFAR, Somayeh, Michal PIORKOWSKI und Krzysztof KRYSZCZUK, 2017. Bayesian framework for mobility pattern discovery using mobile network events. In: 2017 25th European Signal Processing Conference (EUSIPCO). Conference paper. IEEE. 2017. S. 1105–1109. ISBN 978-0-9928626-7-1
Danafar, Somayeh, Michal Piorkowski, and Krzysztof Kryszczuk. 2017. “Bayesian Framework for Mobility Pattern Discovery Using Mobile Network Events.” Conference paper. In 2017 25th European Signal Processing Conference (EUSIPCO), 1105–9. IEEE. https://doi.org/10.21256/zhaw-4053.
Danafar, Somayeh, et al. “Bayesian Framework for Mobility Pattern Discovery Using Mobile Network Events.” 2017 25th European Signal Processing Conference (EUSIPCO), IEEE, 2017, pp. 1105–9, https://doi.org/10.21256/zhaw-4053.


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