A game theory-assisted machine learning methodology for subscriber churn behaviors detection

At the end of November 2019,China officially implemented the number portability policy (MNP) that has been in trial for 9 years.The policy will strengthen the liquidity and competitiveness of the telecommunication market,making the problem of subscriber churn more prominent.A game theory-assisted ma...

Full description

Saved in:
Bibliographic Details
Main Authors: Ye OUYANG, Aidong YANG, Fanyu MENG
Format: Article
Language:zho
Published: Beijing Xintong Media Co., Ltd 2020-06-01
Series:Dianxin kexue
Subjects:
Online Access:http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020164/
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:At the end of November 2019,China officially implemented the number portability policy (MNP) that has been in trial for 9 years.The policy will strengthen the liquidity and competitiveness of the telecommunication market,making the problem of subscriber churn more prominent.A game theory-assisted machine learning methodology was proposed,verified and commercialized timely,which could help mobile network operator (MNO) actively respond to competition in the MNP market.The proposed methodology provides MNO with a machine learning model to detect subscriber portability and give differentiated treatment.Experimental results show that the proposed methodology can guide MNOs to make a targeted MNP strategy,and precisely identify “abnormal” subscribers who tend to churn-out and potential new subscribers who may churn-in.In addition,the proposed methodology has been successfully commercialized,greatly improving the marketing efficiency of operators,increasing user satisfaction,and reducing the loss of users by about 50% for a tier-1 MNO in China.
ISSN:1000-0801