Quantifying and Leveraging User Fatigue for Interventions in Recommender Systems-Reference-Cited by-同舟云学术

Quantifying and Leveraging User Fatigue for Interventions in Recommender Systems

Published:2023-07-18 Issue: Volume: Page:
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Container-title:Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Sagtani Hitesh¹^ORCID,Jhawar Madan Gopal¹^ORCID,Gupta Akshat¹^ORCID,Mehrotra Rishabh¹^ORCID

Affiliation:

1. Sharechat, Bengaluru, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539618.3592044

Reference26 articles.

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2. Customer Churn Prediction Model and Identifying Features to Increase Customer Retention based on User Generated Content;el Kassem Essam Abou;IJACSA) International Journal of Advanced Computer Science and Applications,2020

3. Churn prediction modeling in mobile telecommunications industry using decision trees;Brandusoiu Ionut;Journal of Computer Science and Control Systems,2013

4. Using Survival Models to Estimate User Engagement in Online Experiments

5. Analysis of customer churn prediction in telecom industry using decision trees and logistic regression

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