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conference paper
A User Centered News Recommendation System
October 5, 2021
HUMAN '21: Proceedings of the 4th Workshop on Human Factors in Hypertext
Spending an uncontrolled quantity and quality of time on digital information sites is affecting our well-being and can lead to serious problems in the long term. In this paper, we present a sequential recommendation framework that uses deep reinforcement learning to capture the users' short and long-term interests, with a proposed use case of blending social news with recommended micro-learning informative news items that can help users derive useful outcomes out of their presence online.
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human21.pdf
Type
postprint
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restricted
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copyright
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810.37 KB
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Adobe PDF
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