Employee Churn Retention System Using Association Rule Mining Techniques-Reference-Cited by-同舟云学术

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Employee Churn Retention System Using Association Rule Mining Techniques

Published:2023-11-01 Issue: Volume: Page:1-5
ISSN:
Container-title:2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE)
language:
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Author:

S Palanikumar¹,Queen M.P. Flower²,H B Resmi³,Suniram A. Salinda Eveline⁴

Affiliation:

1. Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College,Department of Computer Science and Business Systems,Chennai,Tamilnadu,India,600062

2. SRM TRP Engineering College,Department of Electrical and Electronics Engineering,Trichy,621105

3. LBS Institute of Technology,Department of Electronics and Communication,Kerala,India,695012

4. St. Alphonsa College of Arts and Science College,Department of Computer Science,Soosaipuram,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10368386/10368609/10369747.pdf?arnumber=10369747

Reference17 articles.

1. A review of the literature on employee turnover;Ongori,2007

2. Analysis of Data on Staff Turnover Using Association Rules and Predictive Techniques

3. The truth about turnover;Smith;Business Journal,2017

4. Analysis of Data on Staff Turnover Using Association Rules and Predictive Techniques

5. New insights into churn prediction in the telecommunication sector: A profit driven data mining approach

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