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Mining Over Air: Wireless Communication Networks Analytics

  • Ye Ouyang
  • Mantian Hu
  • Alexis Huet
  • Zhongyuan Li

Table of contents

  1. Front Matter
    Pages i-xi
  2. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 1-11
  3. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 13-38
  4. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 39-51
  5. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 53-67
  6. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 69-81
  7. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 83-95
  8. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 97-106
  9. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 107-125
  10. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 127-138
  11. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 139-154
  12. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 155-171
  13. Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
    Pages 173-196

About this book

Introduction

This book introduces the concepts, applications and development of data science in the telecommunications industry by focusing on advanced machine learning and data mining methodologies in the wireless networks domain. Mining Over Air  describes the problems and their solutions for wireless network performance and quality, device quality readiness and returns analytics, wireless resource usage profiling, network traffic anomaly detection, intelligence-based self-organizing networks, telecom marketing, social influence, and other important applications in the telecom industry. 

Written by authors who study big data analytics in wireless networks and telecommunication markets from both industrial and academic perspectives, the book targets the pain points in telecommunication networks and markets through big data. 

Designed for both practitioners and researchers, the book explores the intersection between the development of new engineering  technology and uses data from the industry to understand consumer behavior. It combines engineering savvy with insights about human behavior. Engineers will understand how the data generated from the technology can be used to understand the consumer behavior and social scientists will get a better understanding of the data generation process.


Keywords

telecommunications 4G 4/5G networks 5G LTE wireless analytics data mining machine learning Analytics for Telecom big data artificial intelligence LTE network performance network analytics telecommunication networks Communications Service Providers device return rate social influence Contagious Churn Network Based Targeting VoLTE Voice Quality

Authors and affiliations

  • Ye Ouyang
    • 1
  • Mantian Hu
    • 2
  • Alexis Huet
    • 3
  • Zhongyuan Li
    • 4
  1. 1.Verizon WirelessBasking RidgeUSA
  2. 2.Chinese University of Hong KongShatinHong Kong
  3. 3.University of LyonLyonFrance
  4. 4.Verizon WirelessBasking RidgeUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-92312-3
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-92311-6
  • Online ISBN 978-3-319-92312-3
  • Buy this book on publisher's site
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