Authors:
- Leverages the power of machine learning and data mining for studying problems in telecommunication networks that cannot be addressed by the traditional methods in telecom space
- Includes methods, solutions, and algorithms that smoothly bridge data science to wireless technologies
- Uses analytics methods and case studies based on state-of-the-art research and applications in 4/5G wireless technologies, machine learning, and data mining
- Maximizes reader insight into the industry from both engineering and social science perspectives
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Table of contents (12 chapters)
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Front Matter
About this book
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
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Verizon Wireless, Basking Ridge, USA
Ye Ouyang, Zhongyuan Li
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Chinese University of Hong Kong, Shatin, Hong Kong
Mantian Hu
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University of Lyon, Lyon, France
Alexis Huet
About the authors
Dr. Ye Ouyang is the youngest Fellow in Verizon history, working on the forefront of cutting edge wireless technologies, artificial intelligence, and data science space. Dr. Ouyang has distinguished experience spanning scientist, researcher, developer, architect, R&D manager, and thought leader.
Dr. Ouyang is leading the Wireless Artificial Intelligence and Big Data team in Verizon Headquarters. Dr. Ouyang was awarded Verizon Fellow title (Verizon’s highest commendation for technical excellence) due to his contributions to wireless AI & big data to improve the performance, quality, reliability, robustness, and scalability of Verizon's networks and devices. His research lies in wireless data science and artificial intelligence, with a focus on 3G/4G LTE/5G networks & device performance, network capacity, traffic patterns, user behaviors, and network & device service quality through simulation, data mining, statistical modeling,machine learning & deep learning techniques.
Dr. Ouyang serves as IEEE Big Data Standard Standing Committee Member (IEEE BDSC), Chair of Device Analytics Working Group of IEEE Big Data Standard Committee, Chair of Industry Relations of IEEE 5G Summit, Industry Chair of IEEE Sarnoff, Workshop Chair of IEEE ICNC, Chair of Executive Forum of IEEE Globecom, Chair of Big Data Committee of IEEE WTS and IEEE WOCC Conferences, Corporate Representative in ETSI, 3GPP and other standard bodies, and TPC for many leading journals, transactions, and magazines.
Dr. Ouyang authored 20+ academic papers, 3 book chapters, 2 books, and 30+ patents. He holds a Master of Science from Tufts University in Massachusetts, USA, a Master of Science from Columbia University, New York, USA, and a Doctor of Philosophy from Stevens Institute of Technology in New Jersey, USA.
Professor Mantian Hu (Mandy) is assistant professor in the Department of Marketing at the Chinese University of Hong Kong. She was the winner of the 2011 Doctoral Dissertation Proposal Competition sponsored by Society for Marketing Advances (USA). Her research focuses on using the cutting-edge empirical models to study and explain consumer behaviors in industries such as telecommunication, automobile and e-commerce. In particular, she is interested in the effects of social network, word-of-mouth, search and learning on influencing consumer behavior. Her research has been published in Marketing Science, The International Journal of Research in Marketing and other leading international journals. She serves as Honorary Advisor of Hong Kong Digital Analytics Association and provides consulting services to marketing research firms, telecom companies and handset manufacturers. Professor Hu received PhD from Stern School of Business at New York University in 2012.
Zhongyuan Li is a data scientistat Verizon Wireless in its New Jersey headquarters. He was previously a research engineer at LSIS (Formerly LG Industrial Systems) in Korea, and a software engineer at the State Grid Corporation in China.
Zhongyuan received his Master’s degree in Computer Engineering from Stevens Institute of Technology in New Jersey, USA, and holds a Master of Science in Electrical and Computer Engineering from Sungkyunkwan University, Korea.
Zhongyuan has published more than 10 papers focusing on machine learning, artificial intelligence and ubiquitous computing. He serves as technical program committee member in IEEE Wireless Telecommunications Symposium and IEEE International Conference on Industrial Internet. He is also a certified professional big data developer and software programmer, organized and participated in design and development of many national level data analytic systems and software systems in both power utility and telecommunication industry.
Bibliographic Information
Book Title: Mining Over Air: Wireless Communication Networks Analytics
Authors: Ye Ouyang, Mantian Hu, Alexis Huet, Zhongyuan Li
DOI: https://doi.org/10.1007/978-3-319-92312-3
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-92311-6Published: 11 August 2018
Softcover ISBN: 978-3-030-06403-7Published: 12 January 2019
eBook ISBN: 978-3-319-92312-3Published: 27 July 2018
Edition Number: 1
Number of Pages: XI, 196
Number of Illustrations: 21 b/w illustrations, 51 illustrations in colour
Topics: Computer Communication Networks, Data Mining and Knowledge Discovery, Algorithm Analysis and Problem Complexity