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Wireless Personal Communications
Published in: Wireless Personal Communications 3/2018

30-08-2018 | Editorial

Wireless Personal Communications: Machine Learning for Big Data Processing in Mobile Internet

Authors: Jun Guo, Zheng-Hua Tan, Sung Ho Cho, Guoqiang Zhang

Published in: Wireless Personal Communications | Issue 3/2018

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Excerpt

With the rapid development of the Internet, academic researches and industrial applications are ever progressing in numbers and generating a massive amount of multi-modal data from multiple sources. The most prominent example is the mobile Internet, where increasingly more data sets and data streams, such as image, audio, social media, are collected, transmitted, and analyzed. These big data collected from a mobile environment allow researchers to learn and understand significant characteristics that traditional data cannot provide. Hence, mobile big data bring us huge opportunities to understand our world more precisely as well as challenges to analyze, process, store, and transmit such a massive amount of data. In order to analyze and understand mobile big data, the developments of related theories, frameworks, models, and algorithms are crucial. The scope of this special issue is to provide machine learning-based theoretical foundations as well as novel models and algorithms to solve these challenges. …
next article Machine Learning Based Big Data Processing Framework for Cancer Diagnosis Using Hidden Markov Model and GM Clustering

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Metadata
Title
Wireless Personal Communications: Machine Learning for Big Data Processing in Mobile Internet
Authors
Jun Guo
Zheng-Hua Tan
Sung Ho Cho
Guoqiang Zhang
Publication date
30-08-2018
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 3/2018
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-018-5916-x

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