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CrowdInt-JAIHC 2017 : Special Issue: Extracting Crowd Intelligence from Pervasive and Social Big Data [JAIHC] | |||||||||||||||
Link: https://sites.google.com/site/wangleye/home/files/JAIHC-SI-crowd_intelligence-CFP%20-%20formal%20format.pdf?attredirects=0 | |||||||||||||||
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Call For Papers | |||||||||||||||
Special Issue on Journal of Ambient Intelligence and Humanized Computing (IF: 0.835)
Extracting Crowd Intelligence from Pervasive and Social Big Data With the prevalence of ubiquitous computing devices (smartphones, wearable devices, etc.) and social network services (Facebook, Twitter, etc.), humans are generating massive digital traces continuously in their daily life. Considering the invaluable crowd intelligence residing in these pervasive and social big data, a spectrum of opportunities are emerging to enable promising smart applications for easing individual life, increasing company profit, as well as facilitating city development. However, the nature of big data also poses fundamental challenges on the techniques and applications relying on the pervasive and social big data from multiple perspectives such as algorithm effectiveness, computation speed, energy efficiency, user privacy, server security, data heterogeneity and system scalability. Tacking these challenges is the key for successfully designing and implementing crowd-intelligence empowered applications and services from pervasive and social big data. This special issue aims to present the state-of-the-art research achievements in addressing the previous challenges in applying pervasive and social big data. Submission Guidelines: Manuscripts should be submitted online at https://www.editorialmanager.com/aihc/default.aspx. All the papers will be peer-reviewed following the journal reviewing procedures. Authors have to select the Article Type “SI: crowd intelligence” in the submission system. Guest Editors: Dr. Leye Wang (Corresponding GE) Postdoc Researcher Hong Kong University of Science and Technology, Hong Kong, China Email: wangleye@gmail.com Associate Prof. Vincent Gauthier CNRS SAMOVAR, Telecom SudParis, University Paris-Saclay, Evry, France Email: vincent.gauthier@telecom-sudparis.eu Associate Prof. Guanling Chen University of Massachusetts Lowell, Massachusetts, USA Email: glchen@cs.uml.edu Dr. Luis Moreira-Matias Senior Researcher NEC Research Labs, Heidelberg, Germany Email: luis.moreira.matias@gmail.com |
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