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Mining over airwireless communicatio...

Ouyang, Ye.

Mining over airwireless communication networks analytics /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mining over airby Ye Ouyang ... [et al.].
其他題名:	wireless communication networks analytics /
其他作者:	Ouyang, Ye.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	xi, 196 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Data mining.
電子資源:	http://dx.doi.org/10.1007/978-3-319-92312-3
ISBN:	9783319923123$q(electronic bk.)

Mining over airwireless communication networks analytics /
Mining over airwireless communication networks analytics /[electronic resource] :by Ye Ouyang ... [et al.]. - Cham :Springer International Publishing :2018. - xi, 196 p. :ill., digital ;24 cm.

Wireless Networks -- Artificial Intelligence -- Big Data -- Machine Learning -- Long Term Evolution (LTE) -- The 5th Generation (5G) -- Self-Organizing Networks (SON) -- Quality of Experience (QoE) -- Network Performance -- Data Analytics.

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.

ISBN: 9783319923123$q(electronic bk.)

Standard No.: 10.1007/978-3-319-92312-3doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

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