Artificial Intelligence Paradigm for Customer Experience Management in Next-Generation Networks: Challenges and Perspectives

被引:20
|
作者
Gacanin, Haris [1 ]
Wagner, Mark [1 ]
机构
[1] Nokia Bell Labs, Berkeley Hts, NJ 07922 USA
来源
IEEE NETWORK | 2019年 / 33卷 / 02期
关键词
QUALITY; QOE;
D O I
10.1109/MNET.2019.1800015
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
With the advancements of next-generation programmable networks, traditional rule-based decision-making may not be able to adapt effectively to changing network and customer requirements and provide an optimal customer experience. CEM components and implementation challenges with respect to operator, network, and business requirements must be understood to meet required demands. This article gives an overview of CEM components and their design challenges. We elaborate on data analytics and artificial intelligence driven CEM and their functional differences. This overview provides a path toward an autonomous CEM framework in next-generation networks and sets the groundwork for future enhancements.
引用
收藏
页码:188 / 194
页数:7
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