Guest Editorial: Special Section on Embracing Artificial Intelligence for Network and Service Management

被引：5

作者：

Lutfiyya, Hanan ^{[1
]}

Birke, Robert ^{[2
]}

Casale, Giuliano ^{[3
]}

Dhamdhere, Amogh ^{[4
]}

Hwang, Jinho ^{[5
]}

Inoue, Takeru ^{[6
]}

Kumar, Neeraj ^{[7
]}

Puthal, Deepak ^{[8
]}

Zincir-Heywood, Nur ^{[9
]}

机构：

[1] Western Univ, Dept Comp Sci, London, ON N6A 3K7, Canada

[2] ABB Res, CH-5405 Baden, Switzerland

[3] Imperial Coll London, Dept Comp, London SW7 2BX, England

[4] Amazon Com Inc, Amazon Web Serv, Seattle, WA USA

[5] Facebook, New York, NY 10003 USA

[6] NTT Corp, NTT Network Innovat Labs, Yokosuka, Kanagawa, Japan

[7] Thapar Inst Engn & Technol, Dept Comp Sci & Engn, Patiala 147004, Punjab, India

[8] Newcastle Univ, Sch Comp, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

[9] Dalhousie Univ, Dept Comp Sci, Halifax, NS B3H 4R2, Canada

来源：

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT | 2021年 / 18卷 / 04期

关键词：

Reinforcement learning; Deep learning; Resource management; Optimization; Real-time systems; Internet of Things; Cloud computing; BIG DATA ANALYTICS; EDITORIAL SPECIAL-ISSUE;

D O I：

10.1109/TNSM.2021.3127543

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Artificial Intelligence (AI) has the potential to leverage the immense amount of operational data of clouds, services, and social and communication networks. As a concrete example, AI techniques have been adopted by telcom operators to develop virtual assistants based on advances in natural language processing (NLP) for interaction with customers and machine learning (ML) to enhance the customer experience by improving customer flow. Machine learning has also been applied to finding fraud patterns which enables operators to focus on dealing with the activity as opposed to the previous focus on detecting fraud.

引用

页码：3936 / 3941

页数：6

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