一种博弈论辅助的机器学习算法检测用户流失行为

欧阳晔; 杨爱东; 孟凡语

doi:10.11959/j.issn.1000-0801.2020164

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一种博弈论辅助的机器学习算法检测用户流失行为

研究与开发 | 更新时间：2024-06-05

- 一种博弈论辅助的机器学习算法检测用户流失行为
- A game theory-assisted machine learning methodology for subscriber churn behaviors detection
- 电信科学 2020年36卷第6期页码：79-89
- 作者机构：
  
  1. 亚信科技（中国）有限公司通信人工智能创新实验室，北京 100193
  2. 加州大学伯克利分校电子工程与计算机科学系，旧金山伯克利 94720
- 作者简介：
  
  [ "欧阳晔（1981- ），男，博士，亚信科技（中国）有限公司首席技术官，国家特聘专家，北京市政府特聘专家，主要研究方向为移动通信、人工智能、数据科学、科技研发创新与管理" ]
  [ "杨爱东（1984- ），男，博士，亚信科技（中国）有限公司通信人工智能实验室数据科学家，主要研究方向为5G通信人工智能技术、超宽带无线通信技术、高级信号处理技术、机器学习与深度学习" ]
  [ "孟凡语（1998- ），男，美国加州大学伯克利分校电子工程与计算机科学系在读，主要研究方向为机器学习与深度学习" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2020164
  中图分类号： TP181
- 网络出版日期：2020-06，
  
  纸质出版日期：2020-06-20
- 稿件说明：
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欧阳晔, 杨爱东, 孟凡语. 一种博弈论辅助的机器学习算法检测用户流失行为[J]. 电信科学, 2020,36(6):79-89.

Ye OUYANG, Aidong YANG, Fanyu MENG. A game theory-assisted machine learning methodology for subscriber churn behaviors detection[J]. Telecommunications science, 2020, 36(6): 79-89.
欧阳晔, 杨爱东, 孟凡语. 一种博弈论辅助的机器学习算法检测用户流失行为[J]. 电信科学, 2020,36(6):79-89. DOI： 10.11959/j.issn.1000-0801.2020164.

Ye OUYANG, Aidong YANG, Fanyu MENG. A game theory-assisted machine learning methodology for subscriber churn behaviors detection[J]. Telecommunications science, 2020, 36(6): 79-89. DOI： 10.11959/j.issn.1000-0801.2020164.

摘要

中国在2019年11月底正式实施已经试行了9年的携号转网政策。该政策会加强通信市场的流动性和竞争性，使运营商用户流失的问题更加突出。提出、验证并产品化了一种博弈论辅助的机器学习方案，以帮助运营商主动应对携号转网市场的竞争。所提方案为运营商提供了一种机器学习模型，检测用户的携转倾向，并给予差异化待遇。实验结果证明，所提方案能够指引运营商制定有针对性的携号转网策略，准确识别出有携入或者携出倾向的“异常”用户。此外，所提方案已被成功地产品化，极大地提高了运营商的营销效率，增加了用户的满意度，为中国某主要运营商减少了大约50%的用户流失。

Abstract

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.

关键词

Keywords

references

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