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Customer Segmentation Using K-Means Algorithm
7 references·1 citing·34 second hop
Customer Segmentation Using K-Means Algorithm (2024)Customer Segmentation Using K-Means Algor…Integration of Machine Learning Techniques to Evaluate Dynamic Customer Segmentation Analysis for Mobile Customers (2017)Integration of Machine Learni…Customer Segmentation Using Clustering and Data Mining Techniques (2013)Customer Segmentation Using C…An effective hybrid learning system for telecommunication churn prediction (2013)An effective hybrid learning …The basis of market segmentation: a critical review of literature (2011)The basis of market segmentat…Customer churn prediction in telecommunications (2011)Customer churn prediction in …Applying Data Mining to Customer Churn Prediction in an Internet Service Provider (2010)Applying Data Mining to Custo…Introduction to Data Mining (2007)Introduction to Data MiningMall Customer Segmentation Engine Through Clustering Analysis (2023)Mall Customer Segmentation En…Path Analysis: Sociological Examples (1966)Applying data mining to telecom churn management (2005)Application of data mining techniques in customer relationship management: A literature review and classification (2008)Early churn prediction with personalized targeting in mobile social games (2017)A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector (2019)The Effectiveness of Hybrid Learning in Improving of Teacher-Student Relationship in Terms of Learning Motivation (2021)Turning telecommunications call details to churn prediction: a data mining approach (2002)Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2006)Customer churn prediction in the telecommunication sector using a rough set approach (2016)In Pursuit of Enhanced Customer Retention Management: Review, Key Issues, and Future Directions (2017)Retention Futility: Targeting High-Risk Customers Might be Ineffective (2017)Comparing performance of feedforward neural nets and K-means for cluster-based market segmentation (1999)Customer Segmentation in XYZ Bank Using K-Means and K-Medoids Clustering (2018)Forecast of individual customer’s demand from a large and noisy dataset (2018)The impact of big data market segmentation using data mining and clustering techniques (2020)Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (2004)Churn Prediction in Telecommunication Industry Using Rough Set Approach (2014)An efficient system for customer churn prediction through particle swarm optimization based feature selection model with simulated annealing (2017)Data-driven agent-based exploration of customer behavior (2017)Improved churn prediction in telecommunication industry using data mining techniques (2014)Using data mining techniques for profiling profitable hotel customers: An application of RFM analysis (2016)An inclusive survey on machine learning for CRM: a paradigm shift (2020)Automatic and Adaptive Segmentation of Customer in R framework using K-means Clustering Technique (2022)Predicting Customer Segment Changes to Enhance Customer Retention: A Case Study for Online Retail using Machine Learning (2023)Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model (1997)Customer portfolio management (CPM) for improved customer relationship management (CRM): Are your customers platinum, gold, silver, or bronze? (2016)Review on Customer Segmentation Technique on Ecommerce (2016)Unveiling Customer Segmentation Patterns in Credit Card Data using K-Means Clustering: A Machine Learning Approach (2023)Soft computing applications in customer segmentation: State-of-art review and critique (2013)Application of K-Means Algorithm for Efficient Customer Segmentation: A Strategy for Targeted Customer Services (2015)Luxe for Less (2015)Using data mining to improve assessment of credit worthiness via credit scoring models (2011)A Methodology for Direct and Indirect Discrimination Prevention in Data Mining (2012)Real-time prediction of online shoppers’ purchasing intention using multilayer perceptron and LSTM recurrent neural networks (2018)
this work references cited by second hop

References

  • 2007Introduction to Data Mining941 cited
  • 2011Customer churn prediction in telecommunications362 cited
  • 2011The basis of market segmentation: a critical review of literature141 cited
  • 2013An effective hybrid learning system for telecommunication churn prediction90 cited
  • 2013Customer Segmentation Using Clustering and Data Mining Techniques75 cited
  • 2010Applying Data Mining to Customer Churn Prediction in an Internet Service Provider68 cited
  • 2017Integration of Machine Learning Techniques to Evaluate Dynamic Customer Segmentation Analysis for Mobile Customers33 cited

Cited by

  • 2023Mall Customer Segmentation Engine Through Clustering Analysis6 cited

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