Supervised machine learning for service providers' classification using multiple criteria in a network architecture environment

被引:0
|
作者
Haddar, Imane [1 ]
Raouyane, Brahim [2 ]
Bellafkih, Mostafa [1 ]
机构
[1] Natl Inst Posts & Telecommun, Rabat, Morocco
[2] Hassan II Univ, Fac Sci Ain Chock, Casablanca, Morocco
来源
PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS: THEORIES AND APPLICATIONS (SITA'18) | 2018年
关键词
Decision tree; machine learning; MCDM; serive providers; service broker; VENDOR SELECTION;
D O I
10.1145/3289402.3289532
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The service selection in a Next Generation Network field remains a challenging problem for service providers, as they have to satisfy customers and keep their earnings. Given the growing number of telecom service providers, the customer is in a dilemma to choose the right service with a fair price. To do so, we propose in this paper a supervised learning algorithm since it is a classification problem. Based on requirements specified in the contract called Service Level Agreement (SLA) in IP Multi-media Service (IMS) network, we ended up choosing the decision trees algorithm for several reasons that we will explore later in this work. This method will assist users in selecting the right service for a better management of contracts between the involved entities.
引用
收藏
页数:7
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