research-article

Prediction of Tariff Package Model Using ROF-LGB Algorithm

Authors:

NaiSong Zheng,

XiaoWei Jiang,

Yibo Ao,

Xi ZhaoAuthors Info & Claims

DSIT 2019: Proceedings of the 2019 2nd International Conference on Data Science and Information Technology

Pages 54 - 58

https://doi.org/10.1145/3352411.3352421

Published: 19 July 2019 Publication History

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Abstract

With the slowing growth of the telecommunication market and the intense competition for existing customers, Customer Churn Management has become a crucial task for all mobile network operators. Recommendation models based on customer behaviors are widely used by operators to provide diverse telecom tariff packages for suitable people and thus improve customer satisfaction. To address the low precision rate and data granularity of prior studies, this study combined rotation forest (ROF) and LightGBM and construct a hybrid algorithm (ROF-LGB). Grid search method was used in parameter tuning, and ten-fold cross-validation method was used to prevent overfitting. Using mobile data generated by operators, ROF-LGB method was tested and compared with other five traditional machine learning methods. The results showed that ROF-LGB method achieved better performance with better precision rate and execution efficiency in telecom tariff package recommendation.

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Xu SHan CRan C(2021)A Time Series Combined Forecasting Model Based on Prophet-LGBM2021 2nd International Conference on Artificial Intelligence and Information Systems10.1145/3469213.3470280(1-6)Online publication date: 28-May-2021
https://dl.acm.org/doi/10.1145/3469213.3470280
Wang XGu YLiu H(2021)A Transfer Learning Method for the Protection of Geographical Indication in China Using an Electronic Nose for the Identification of Xihu Longjing TeaIEEE Sensors Journal10.1109/JSEN.2020.304853421:6(8065-8077)Online publication date: 15-Mar-2021
https://doi.org/10.1109/JSEN.2020.3048534
Jin XLi SZhang WZhu JSun J(2020)Prediction of Soil-Available Potassium Content with Visible Near-Infrared Ray Spectroscopy of Different Pretreatment Transformations by the Boosting AlgorithmsApplied Sciences10.3390/app1004152010:4(1520)Online publication date: 23-Feb-2020
https://doi.org/10.3390/app10041520

Index Terms

Prediction of Tariff Package Model Using ROF-LGB Algorithm
1. Computing methodologies
  1. Symbolic and algebraic manipulation
    1. Symbolic and algebraic algorithms
      1. Combinatorial algorithms

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DSIT 2019: Proceedings of the 2019 2nd International Conference on Data Science and Information Technology

July 2019

280 pages

ISBN:9781450371414

DOI:10.1145/3352411

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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The Hong Kong Polytechnic: The Hong Kong Polytechnic University
Natl University of Singapore: National University of Singapore

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Published: 19 July 2019

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DSIT 2019: 2019 2nd International Conference on Data Science and Information Technology

July 19 - 21, 2019

Seoul, Republic of Korea

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Xu SHan CRan C(2021)A Time Series Combined Forecasting Model Based on Prophet-LGBM2021 2nd International Conference on Artificial Intelligence and Information Systems10.1145/3469213.3470280(1-6)Online publication date: 28-May-2021
https://dl.acm.org/doi/10.1145/3469213.3470280
Wang XGu YLiu H(2021)A Transfer Learning Method for the Protection of Geographical Indication in China Using an Electronic Nose for the Identification of Xihu Longjing TeaIEEE Sensors Journal10.1109/JSEN.2020.304853421:6(8065-8077)Online publication date: 15-Mar-2021
https://doi.org/10.1109/JSEN.2020.3048534
Jin XLi SZhang WZhu JSun J(2020)Prediction of Soil-Available Potassium Content with Visible Near-Infrared Ray Spectroscopy of Different Pretreatment Transformations by the Boosting AlgorithmsApplied Sciences10.3390/app1004152010:4(1520)Online publication date: 23-Feb-2020
https://doi.org/10.3390/app10041520

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The Effect of Package Coupons on Brand Choice: An Epilogue on Profits

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Product marketing prediction based on XGboost and LightGBM algorithm

The Effect of Package Coupons on Brand Choice: An Epilogue on Profits

Prediction and Analysis of Customer Complaints Using Machine Learning Techniques

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