Paywall policy learning in digital news media

Heidar Davoudi, Zana Rashidi, Aijun An, Morteza Zihayat, Gordon Edall
January 2020

Abstract

This paper presents machine learning approaches for optimizing paywall policies in digital news media, balancing revenue generation with user engagement.

Type
Journal article
Publication
IEEE Transactions on Knowledge and Data Engineering

This work applies machine learning techniques to optimize paywall strategies in digital news platforms.

Machine Learning Digital Media Paywall Optimization Revenue Management Policy Learning
Morteza Zihayat
Morteza Zihayat
Principal Investigator

Dr. Morteza Zihayat is a Canada Research Chair (CRC) in Human-Centered AI and Associate Professor at Toronto Metropolitan University, Faculty of Engineering and Architectural Science. He also holds appointments as Adjunct Associate Professor at the University of Waterloo (Management Sciences) and IBM Faculty Fellow at IBM Centre for Advanced Studies. He is the Director of the Human-Centered Machine Intelligence Lab.