SCENE: a scalable two-stage personalized news recommendation system

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DRN: A Deep Reinforcement Learning Framework for News Recommendation (2018, methodology): “Although there are some online recommendation methods [11, 24] that can capture the dynamic change of news features and user preference through online model updates, they only try to optimize the current reward (e.”
NewsEmbed: Modeling News through Pre-trained Document Representations (2021, background): “[37] represents news article using content, access patterns, named entities, popularity and recency.”
News recommender systems - Survey and roads ahead (2018, methodology): “In [108], for example, the authors propose a two-stage recommendation approach in which they apply different clustering techniques to create a hierarchy of news clusters.”
NPA: Neural News Recommendation with Personalized Attention (2019, methodology): “lied CF methods to aggregate news from Usenet. However, pure CF methods usually suffer from the sparsity and the cold-start problems, which are especially significant in news recommendation scenarios [19]. Thus, content-based techniques are usually complementary methods to CF [2, 20, 21, 24, 27, 29,”