Multiobjective Deep Reinforcement Learning for Recommendation Systems

Multiobjective Deep Reinforcement Learning for Recommendation Systems

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Most existing recommendation systems (RSs) are primarily concerned about the accuracy of rating prediction and only recommending popular items. However, other non-accuracy metrics such as novelty and diversity should not be overlooked. Existing multi-objective (MO) RSs employed collaborative filteri...

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Bibliographic Details
Main Authors: Ee Yeo Keat, Nurfadhlina Mohd Sharef, Razali Yaakob, Khairul Azhar Kasmiran, Erzam Marlisah, Norwati Mustapha, Maslina Zolkepli
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
machine learning
multiobjective
recommendation system
Online Access:https://ieeexplore.ieee.org/document/9791369/

Internet

https://ieeexplore.ieee.org/document/9791369/

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