Special issue on extracting crowd intelligence from pervasive and social big data

[...]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...

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Bibliographic Details
Published in:Journal of ambient intelligence and humanized computing 2018-11, Vol.9 (6), p.2009-2010
Main Authors: Wang, Leye, Gauthier, Vincent, Chen, Guanling, Moreira-Matias, Luis
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Automation
Big Data
Computational Intelligence
Decision making
Decision trees
Defense
Editorial
Engineering
Estate agencies
Heterogeneity
Hypertension
Machine learning
Robotics and Automation
Semantics
Smartphones
Social networks
User Interfaces and Human Computer Interaction
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Summary:[...]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. The sixth paper “Recommending property with short days-on-market for estate agency” by Mou et al. proposes an estate with short days-on-market appraisal framework to automatically recommend those estates using transaction data and profile information crawled from websites. The last paper “Semantic place prediction from crowd-sensed mobile phone data” by Celik et al. semantically classifes places visited by smart phone users utilizing the data collected from sensors and wireless interfaces available on the phones as well as phone usage patterns, such as battery level, and time-related information, with machine learning algorithms.
ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-018-0680-z