Customer Profiling and Retention Using Recommendation System and Factor Identification to Predict Customer Churn in Telecom Industry

[1]  Bart Baesens,et al.  Building comprehensible customer churn prediction models with advanced rule induction techniques , 2011, Expert Syst. Appl..

[2]  Ricard Gavaldà,et al.  The Architecture of a Churn Prediction System Based on Stream Mining , 2013, CCIA.

[3]  Gao Hua.  Customer relationship management based on data mining technique — Naive Bayesian classifier , 2011, 2011 International Conference on E-Business and E-Government (ICEE).

[4]  Qiang Yang,et al.  Telco Churn Prediction with Big Data , 2015, SIGMOD Conference.

[5]  R. Rajamohamed,et al.  Improved credit card churn prediction based on rough clustering and supervised learning techniques , 2018, Cluster Computing.

[6]  Thar Baker,et al.  Just-in-time Customer Churn Prediction: With and Without Data Transformation , 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

[7]  Ruey-Shun Chen,et al.  Data Mining Application in Customer Relationship Management of Credit Card Business , 2005, COMPSAC.

[8]  João Falcão e Cunha,et al.  Modeling partial customer churn: On the value of first product-category purchase sequences , 2012, Expert systems with applications.

[10]  Manjit Kaur,et al.  Data Mining as a tool to Predict the Churn Behaviour among Indian bank customers , 2013 .

[11]  Mustafa Mat Deris,et al.  CHURN CLASSIFICATION MODEL FOR LOCAL TELECOMMUNICATION COMPANY BASED ON ROUGH SET THEORY , 2018 .

[12]  Arno De Caigny,et al.  A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees , 2018, Eur. J. Oper. Res..

[13]  A. N. Nandakumar,et al.  A Survey of Customer RelationshipManagement , 2016 .

[14]  Hee-Su Kim,et al.  Determinants of subscriber churn and customer loyalty in the Korean mobile telephony market , 2004 .

[15]  Amir Hussain,et al.  Comparing Oversampling Techniques to Handle the Class Imbalance Problem: A Customer Churn Prediction Case Study , 2016, IEEE Access.

[16]  Ying Huang,et al.  An effective hybrid learning system for telecommunication churn prediction , 2013, Expert Syst. Appl..

[17]  Muhammad Imran,et al.  A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector , 2019, IEEE Access.

[18]  Xiangjun Dong,et al.  K- local maximum margin feature extraction algorithm for churn prediction in telecom , 2017, Cluster Computing.

[19]  David C. Yen,et al.  Data mining techniques for customer relationship management , 2002 .

[20]  Dirk Van den Poel,et al.  Handling class imbalance in customer churn prediction , 2009, Expert Syst. Appl..

[21]  Gavril Toderean,et al.  Methods for churn prediction in the pre-paid mobile telecommunications industry , 2016, 2016 International Conference on Communications (COMM).

[22]  S. Babu.  A Survey on Factors Impacting Churn in Telecommunication using Datamininig Techniques , 2014 .

[23]  Asifullah Khan,et al.  Customer churn prediction for telecommunication: Employing various various features selection techniques and tree based ensemble classifiers , 2012, 2012 15th International Multitopic Conference (INMIC).