International Conference on Information and Knowledge Technology

فارسی

Home / یازدهمین کنفرانس بین المللی فناوری اطلاعات و دانش

Effective Classifier for Predicting Churn in Payment Terminals Using RFM model and Deep Neural Network

Authors :

Mahila Dadfarnia¹ Ali Alemi Matinpour² Monireh Abdoos³

1- دانشگاه یزد 2- تربیت مدرس تهران 3- تربیت مدرس تهران

Keywords :

Payment terminals, Churn prediction, RFM (recency, frequency and monetary), DNN (Deep Neural Network), Genetic Algorithms

Abstract :

In recent years, there is remarkable growing concern for marketing team to retain their customers. This can be achieved by predicting accurately ahead of time, whether a terminal for buying is valuable in the foreseeable future or not. This paper presents the application of Deep Neural Network in the issue of classifying the payment terminals in different branches of Parsian bank specifically. The paper uses real data for classifying various payment terminals in 6 classes of terminal by a 5 layer deep neural network and RFM model. The empirical results reveal that utilizing the deep network generate significantly better accuracy in comparison with other popular methods

List of archived papers

KGLM-QA: A Novel Approach for Knowledge Graph-Enhanced Large Language Models for Question Answering

Alireza Akhavan safaei - Pegah Saboori - Reza Ramezani - Mohammadali Nematbakhsh

Improving Fog Computing Scalability in Software Defined Network using Critical Requests Prediction in IoT

Hajar Ghanbari

Design and Simulation of a New Multiplexer with Energy Analysis in Quantum Cellular Automata Technology

- - -

تحلیل و بررسی تکنیک‌های محاسبات تقریبی

محمد میلاد صیاد - محمد رضا بینش مروستی - سید امیر اصغری

رویکردی در تشخیص خودکار بوهای بد در مدل های معماری سازمانی با استفاده از تحلیل گرافی

زهرا رحیمی تمندگانی - شهره آجودانیان

Classification and Evaluation of Privacy Preserving Data Mining Methods

Negar Nasiri - Mohammadreza Keyvanpour

Distributed coordination protocol for event data exchange in IoT monitoring applications

Behnam Khazael - Hadi Tabatabaee Malazi

Electrophysiological Modeling and Interactive Approaches of Electrical Circuits and Hypergraphs for Understanding Neural Circuit Dynamics

Arian Baymani - Maryam Naderi Soorki

A Hybrid Method to Reduce the Voltage Consumption in the Spiking Neural Networks

Shaghayegh Mehdizadeh saraj - Seyyed Amir Asghari - Mohammadreza Binesh Marvasti

A Blockchain Architecture for Secure, High-Speed P2P Energy Trades with Game-Theoretic Coalition Formation

Amin Aboutalebi Najafabadi - Seyed Hossein Hosseinian

more

Samin Hamayesh - Version 44.2.0