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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

CELoF: WiFi Dwell Time Estimation in Free Environment

verfasst von : Chen Yan, Peng Wang, Haitian Pang, Lifeng Sun, Shiqiang Yang

Erschienen in: MultiMedia Modeling

Verlag: Springer International Publishing

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Abstract

WiFi wireless access has been the basic living need for smart phone users in the era of mobile multimedia. A large number of WiFi hotspots have also developed into an important infrastructure of multimedia accessing in smart city. Learning the dynamic features of free-environment WiFi connections is of great help to both the customization of WiFi connection service and the strategy of mobile multimedia. While mobility prediction attracts much interest in human behavior research which is more focused on fixed environments such as university, home and office, etc., this paper investigates more challenging public regions like shopping malls. A WiFi dwell time estimation method is proposed from a crowdsourcing view, to tackle the lack of contextual information for a single individual in such free environments. This is achieved by a context-embedded longitudinal factorization (CELoF) method based on multi-way tensor factorization and experiments on real dataset demonstrate the efficacy of the proposed solution.

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Vorheriges Kapitel Uyghur Language Text Detection in Complex Background Images Using Enhanced MSERs
Nächstes Kapitel Demographic Attribute Inference from Social Multimedia Behaviors: A Cross-OSN Approach
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Metadaten
Titel
CELoF: WiFi Dwell Time Estimation in Free Environment
verfasst von
Chen Yan
Peng Wang
Haitian Pang
Lifeng Sun
Shiqiang Yang
Copyright-Jahr
2017
Buch
MultiMedia Modeling

Print ISBN: 978-3-319-51810-7

Electronic ISBN: 978-3-319-51811-4

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-51811-4_41

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