mlsanityData to 7 Oct 2026

D-HAN: Dynamic News Recommendation with Hierarchical Attention Network

arXiv 2112.10085 ↗First posted 19 Dec 2021cs.IR cs.AIcited by 1

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Abstract (arXiv)

News recommendation models often fall short in capturing users' preferences due to their static approach to user-news interactions. To address this limitation, we present a novel dynamic news recommender model that seamlessly integrates continuous time information to a hierarchical attention network that effectively represents news information at the sentence, element, and sequence levels. Moreover, we introduce a dynamic negative sampling method to optimize users' implicit feedback. To validate our model's effectiveness, we conduct extensive experiments on three real-world datasets. The results demonstrate the effectiveness of our proposed approach.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 13 of its 50 references that are in the map. First posted on arXiv 19 Dec 2021.

Builds on

13 of 50 references.

References · 13

  1. 2017Attention Is All You Needcited by 59,932
  2. 2019BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformercited by 952
  3. 2015Session-based Recommendations with Recurrent Neural Networkscited by 685
  4. 2017Deep Interest Network for Click-Through Rate Predictioncited by 541
  5. 2018Personalized Top-N Sequential Recommendation via Convolutional Sequence Embeddingcited by 473
  6. 2021A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directionscited by 144
  7. 2018DKN: Deep Knowledge-Aware Network for News Recommendationcited by 137
  8. 2019Neural News Recommendation with Attentive Multi-View Learningcited by 59
  9. 2014POLYGLOT-NER: Massive Multilingual Named Entity Recognitioncited by 32
  10. 2021Personalized News Recommendation: Methods and Challengescited by 30
  11. 2020Session-aware Recommendation: A Surprising Quest for the State-of-the-artcited by 15
  12. 2013Personalized News Recommendation with Context Treescited by 11
1 more
  1. 2020Extreme Classification via Adversarial Softmax Approximationcited by 10

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Citing papers per year: 2025: 1.

1 paper.

  1. 2025A Survey on LLM-based News Recommender Systemscited by 1