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Neural News Recommendation with Attentive Multi-View Learning

arXiv 1907.05576 ↗First posted 12 Jul 2019cs.CL cs.IR cs.LGcited by 59

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Abstract (arXiv)

Personalized news recommendation is very important for online news platforms to help users find interested news and improve user experience. News and user representation learning is critical for news recommendation. Existing news recommendation methods usually learn these representations based on single news information, e.g., title, which may be insufficient. In this paper we propose a neural news recommendation approach which can learn informative representations of users and news by exploiting different kinds of news information. The core of our approach is a news encoder and a user encoder. In the news encoder we propose an attentive multi-view learning model to learn unified news representations from titles, bodies and topic categories by regarding them as different views of news. In addition, we apply both word-level and view-level attention mechanism to news encoder to select important words and views for learning informative news representations. In the user encoder we learn the representations of users based on their browsed news and apply attention mechanism to select informative news for user representation learning. Extensive experiments on a real-world dataset show our approach can effectively improve the performance of news recommendation.

Key facts. Cited by 59 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Jul 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 15; 2022: 13; 2023: 8; 2024: 12; 2025: 10; 2026: 1.

59 papers.

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  1. 2021FedKD: Communication Efficient Federated Learning via Knowledge Distillationcited by 185
  2. 2021A Survey on Accuracy-oriented Neural Recommendation: From Collaborative Filtering to Information-rich Recommendationcited by 59
  3. 2023ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Modelscited by 54
  4. 2023Prompt Learning for News Recommendationcited by 25
  5. 2022FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learningcited by 23
  6. 2021Training Large-Scale News Recommenders with Pretrained Language Models in the Loopcited by 18
  7. 2021Rethinking InfoNCE: How Many Negative Samples Do You Need?cited by 18
  8. 2021NewsBERT: Distilling Pre-trained Language Model for Intelligent News Applicationcited by 17
  9. 2023LKPNR: LLM and KG for Personalized News Recommendation Frameworkcited by 13
  10. 2023Scalable Neural Contextual Bandit for Recommender Systemscited by 12
  11. 2021Why Do We Click: Visual Impression-aware News Recommendationcited by 10
  12. 2023Going Beyond Local: Global Graph-Enhanced Personalized News Recommendationscited by 10
38 more
  1. 2021USER: A Unified Information Search and Recommendation Model based on Integrated Behavior Sequencecited by 9
  2. 2021Neural News Recommendation with Collaborative News Encoding and Structural User Encodingcited by 7
  3. 2022RADio -- Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendationscited by 7
  4. 2022DIGAT: Modeling News Recommendation with Dual-Graph Interactioncited by 7
  5. 2024SPAR: Personalized Content-Based Recommendation via Long Engagement Attentioncited by 6
  6. 2022Semi-FairVAE: Semi-supervised Fair Representation Learning with Adversarial Variational Autoencodercited by 5
  7. 2023Modeling User Viewing Flow Using Large Language Models for Article Recommendationcited by 4
  8. 2024EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendationscited by 4
  9. 2024News Recommendation with Category Description by a Large Language Modelcited by 4
  10. 2024News Without Borders: Domain Adaptation of Multilingual Sentence Embeddings for Cross-lingual News Recommendationcited by 4
  11. 2025Diffusion-based Multi-modal Synergy Interest Network for Click-through Rate Predictioncited by 4
  12. 2021Deep Dynamic Neural Network to trade-off between Accuracy and Diversity in a News Recommender Systemcited by 3
  13. 2021Aspect-driven User Preference and News Representation Learning for News Recommendationcited by 3
  14. 2022Few-shot News Recommendation via Cross-lingual Transfercited by 3
  15. 2022VLSNR:Vision-Linguistics Coordination Time Sequence-aware News Recommendationcited by 3
  16. 2024PerSEval: Assessing Personalization in Text Summarizerscited by 3
  17. 2021From Implicit to Explicit feedback: A deep neural network for modeling sequential behaviours and long-short term preferences of online userscited by 2
  18. 2021Neural News Recommendation with Event Extractioncited by 2
  19. 2022Targeted Data Poisoning Attack on News Recommendation System by Content Perturbationcited by 2
  20. 2022Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedbackcited by 2
  21. 2023CROWN: A Novel Approach to Comprehending Users' Preferences for Accurate Personalized News Recommendationcited by 2
  22. 2024JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced Transformercited by 2
  23. 2024Are Large Language Models In-Context Personalized Summarizers? Get an iCOPERNICUS Test Done!cited by 2
  24. 2025Fact-Preserved Personalized News Headline Generationcited by 2
  25. 2025Co-NAML-LSTUR: A Combined Model with Attentive Multi-View Learning and Long- and Short-term User Representations for News Recommendationcited by 2
  26. 2021Learning to Select Historical News Articles for Interaction based Neural News Recommendationcited by 1
  27. 2021D-HAN: Dynamic News Recommendation with Hierarchical Attention Networkcited by 1
  28. 2021On the Overlooked Significance of Underutilized Contextual Features in Recent News Recommendation Modelscited by 1
  29. 2022GateFormer: Speeding Up News Feed Recommendation with Input Gated Transformerscited by 1
  30. 2022Quality-aware News Recommendationcited by 1
  31. 2022Understanding the Relation of User and News Representations in Content-Based Neural News Recommendationcited by 1
  32. 2023PUNR: Pre-training with User Behavior Modeling for News Recommendationcited by 1
  33. 2024Time Matters: Enhancing Pre-trained News Recommendation Models with Robust User Dwell Time Injectioncited by 1
  34. 2024Peeling Back the Layers: An In-Depth Evaluation of Encoder Architectures in Neural News Recommenderscited by 1
  35. 2025A Survey on LLM-based News Recommender Systemscited by 1
  36. 2025Personalized News Recommendation with Multi-granularity Candidate-aware User Modelingcited by 1
  37. 2022Deep Multi-View Learning for Tire Recommendationcited by 0
  38. 2022IGNiteR: News Recommendation in Microblogging Applications (Extended Version)cited by 0

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