Integrating Stochastic Models into News Recommender Systems: A Comparative Study with Hybrid Approaches
Resumo
Recommender systems are essential for handling information overload in online newspapers, where the lack of explicit feedback and the need for real-time updates limit computationally expensive methods. This work investigates how contextualization based on stochastic models that capture the sequential and uncertain nature of reading behavior improves news recommender systems. Using real access logs and a simulation environment, we evaluate these models across multiple metrics. The results show that stochastic models outperform traditional approaches, especially in personalization and diversity, and that combining them with hybrid methods yields the best performance.
Palavras-chave:
News Recommender Systems, Session-Based Recommendation, Stochastic Models, Markov Models, Sequential User Behavior, Context-Aware Recommendation, Implicit Feedback, Hybrid Recommender Systems
Referências
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Campos, P. G., Díez, F., and Cantador, I. (2014). Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols. User Modeling and User-Adapted Interaction, 24(1-2):67–119.
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Champiri, Z. D., Shahamiri, and Salim (2015). A systematic review of scholar context-aware recommender systems. Expert Systems with Applications, 42(3):1743–1758.
Constantinides, M. and Dowell, J. (2018). A framework for interaction-driven user modeling of mobile news reading behaviour. In Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, page 33–41. ACM.
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Koo, B., Jeon, H., and Kang, U. (2021). Pgt: news recommendation coalescing personal and global temporal preferences. Knowledge and Information Systems, 63:3139–3158.
Li, J., Zhu, J., Bi, Q., Cai, G., Shang, L., Dong, Z., Jiang, X., and Liu, Q. (2022). MINER: Multi-interest matching network for news recommendation. In Findings of the Association for Computational Linguistics: ACL 2022, pages 343–352. ACL.
Li, L., Zheng, L., Yang, F., and Li, T. (2014). Modeling and broadening temporal user interest in personalized news recommendation. Expert Systems with Applications, 41:3168–3177.
Liu, J., Dolan, P., and Pedersen, E. R. (2010). Personalized news recommendation based on click behavior. In Proceedings of the 15th International Conference on Intelligent User Interfaces, pages 31–40. ACM.
Lv, P., Zhang, Q., Shi, L., Guan, Z., Fan, Y., Li, J., Zhong, K., and Deveci, M. (2024). Exploring on role of location in intelligent news recommendation from data analysis perspective. Information Sciences, 662.
Maksai, A., Garcin, F., and Faltings, B. (2015). Predicting online performance of news recommender systems through richer evaluation metrics. In Proceedings of the 9th ACM Conference on Recommender Systems, pages 179–186. ACM.
Meng, Q., Yan, H., Liu, B., Sun, X., Hu, M., and Cao, J. (2023). Recognize news transition from collective behavior for news recommendation. ACM Transactions on Information Systems, 41.
Moreira, G. D. S. P., Ferreira, F., and Cunha, A. M. D. (2018). News session-based recommendations using deep neural networks. In ACM International Conference Proceeding Series, pages 15–23. ACM.
Park, C. (2025). Llm as user simulator: Towards training news recommender without real user interactions. In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, page 3080–3084. ACM.
Pu, Z. and Beam, M. A. (2024). The impacts of relevance of recommendations and goal commitment on user experience in news recommender design. User Modeling and User-Adapted Interaction, 34(4):925–953.
Raza, S. and Ding, C. (2022). News recommender system: a review of recent progress, challenges, and opportunities. Artif. Intell. Rev., 55(1):749–800.
Ren, S. and Shi, C. (2022). A news recommendation model based on time awareness and news relevance. In 23rd International Conference on Information Reuse and Integration for Data Science (IRI), page 35–40, USA. IEEE Press.
Sheu, H. S., Chu, Z., Qi, D., and Li, S. (2022). Knowledge-guided article embedding refinement for session-based news recommendation. IEEE Transactions on Neural Networks and Learning Systems, 33:7921–7927.
Symeonidis, P., Chaltsev, D., Berbague, C., and Zanker, M. (2022). Sequence-aware news recommendations by combining intrawith inter-session user information. Information Retrieval Journal, 25:461–480.
Veloso, B. M., Assunção, R. M., Ferreira, A. A., and Ziviani, N. (2019). In search of a stochastic model for the e-news reader. ACM Transactions on Knowledge Discovery from Data, 13(6):1–27.
Wang, Y., Sang, L., Zhang, Y., and Zhang, Y. (2025). Intent representation learning with large language model for recommendation. In Proceedings of the 48th International ACM SIGIR, page 1870–1879. ACM.
Wu, C., Wu, F., Huang, Y., and Xie, X. (2023). Personalized news recommendation: Methods and challenges. ACM Trans. Inf. Syst., 41(1).
Xin, R., Chen, X., Jiang, D., He, Y., Ou, Z., Liu, P., Han, Z., and Song, M. (2022). El-rec: Enhanced user and news interaction for news recommendation. In 8th International Conference on Cloud Computing and Intelligent Systems, pages 355–359. IEEE.
Campos, P. G., Díez, F., and Cantador, I. (2014). Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols. User Modeling and User-Adapted Interaction, 24(1-2):67–119.
Çano, E. and Morisio, M. (2017). Hybrid recommender systems: A systematic literature review. Intelligent Data Analysis, 21(6):1487–1524.
Cavalcante, P. S. and Pinheiro, W. A. (2013). Mecanismo de encadeamento de notícias por reconhecimento de implicação textual. In SBBD (Short Papers), pages 27–1.
Champiri, Z. D., Shahamiri, and Salim (2015). A systematic review of scholar context-aware recommender systems. Expert Systems with Applications, 42(3):1743–1758.
Constantinides, M. and Dowell, J. (2018). A framework for interaction-driven user modeling of mobile news reading behaviour. In Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, page 33–41. ACM.
Das, A. S., Datar, M., Garg, A., and Rajaram, S. (2007). Google news personalization: scalable online collaborative filtering. In Proceedings of the 16th International Conference on World Wide Web, page 271–280. ACM.
Epure, E. V., Kille, B., Ingvaldsen, J. E., Deneckere, R., Salinesi, C., and Albayrak, S. (2017). Recommending personalized news in short user sessions. In Proceedings of the Eleventh ACM Conference on Recommender Systems, page 121–129. ACM.
Garcin, F., Dimitrakakis, C., and Faltings, B. (2013). Personalized news recommendation with context trees. In RecSys 2013 Proceedings of the 7th ACM Conference on Recommender Systems, pages 105–112. ACM.
Ji, Z., Wu, M., Yang, H., and Íñigo, J. E. A. (2021). Temporal sensitive heterogeneous graph neural network for news recommendation. Future Generation Computer Systems, 125:324–333.
Karimi, M., Jannach, D., and Jugovac, M. (2018). News recommender systems – survey and roads ahead. Information Processing & Management, 54(6):1203–1227.
Koo, B., Jeon, H., and Kang, U. (2021). Pgt: news recommendation coalescing personal and global temporal preferences. Knowledge and Information Systems, 63:3139–3158.
Li, J., Zhu, J., Bi, Q., Cai, G., Shang, L., Dong, Z., Jiang, X., and Liu, Q. (2022). MINER: Multi-interest matching network for news recommendation. In Findings of the Association for Computational Linguistics: ACL 2022, pages 343–352. ACL.
Li, L., Zheng, L., Yang, F., and Li, T. (2014). Modeling and broadening temporal user interest in personalized news recommendation. Expert Systems with Applications, 41:3168–3177.
Liu, J., Dolan, P., and Pedersen, E. R. (2010). Personalized news recommendation based on click behavior. In Proceedings of the 15th International Conference on Intelligent User Interfaces, pages 31–40. ACM.
Lv, P., Zhang, Q., Shi, L., Guan, Z., Fan, Y., Li, J., Zhong, K., and Deveci, M. (2024). Exploring on role of location in intelligent news recommendation from data analysis perspective. Information Sciences, 662.
Maksai, A., Garcin, F., and Faltings, B. (2015). Predicting online performance of news recommender systems through richer evaluation metrics. In Proceedings of the 9th ACM Conference on Recommender Systems, pages 179–186. ACM.
Meng, Q., Yan, H., Liu, B., Sun, X., Hu, M., and Cao, J. (2023). Recognize news transition from collective behavior for news recommendation. ACM Transactions on Information Systems, 41.
Moreira, G. D. S. P., Ferreira, F., and Cunha, A. M. D. (2018). News session-based recommendations using deep neural networks. In ACM International Conference Proceeding Series, pages 15–23. ACM.
Park, C. (2025). Llm as user simulator: Towards training news recommender without real user interactions. In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, page 3080–3084. ACM.
Pu, Z. and Beam, M. A. (2024). The impacts of relevance of recommendations and goal commitment on user experience in news recommender design. User Modeling and User-Adapted Interaction, 34(4):925–953.
Raza, S. and Ding, C. (2022). News recommender system: a review of recent progress, challenges, and opportunities. Artif. Intell. Rev., 55(1):749–800.
Ren, S. and Shi, C. (2022). A news recommendation model based on time awareness and news relevance. In 23rd International Conference on Information Reuse and Integration for Data Science (IRI), page 35–40, USA. IEEE Press.
Sheu, H. S., Chu, Z., Qi, D., and Li, S. (2022). Knowledge-guided article embedding refinement for session-based news recommendation. IEEE Transactions on Neural Networks and Learning Systems, 33:7921–7927.
Symeonidis, P., Chaltsev, D., Berbague, C., and Zanker, M. (2022). Sequence-aware news recommendations by combining intrawith inter-session user information. Information Retrieval Journal, 25:461–480.
Veloso, B. M., Assunção, R. M., Ferreira, A. A., and Ziviani, N. (2019). In search of a stochastic model for the e-news reader. ACM Transactions on Knowledge Discovery from Data, 13(6):1–27.
Wang, Y., Sang, L., Zhang, Y., and Zhang, Y. (2025). Intent representation learning with large language model for recommendation. In Proceedings of the 48th International ACM SIGIR, page 1870–1879. ACM.
Wu, C., Wu, F., Huang, Y., and Xie, X. (2023). Personalized news recommendation: Methods and challenges. ACM Trans. Inf. Syst., 41(1).
Xin, R., Chen, X., Jiang, D., He, Y., Ou, Z., Liu, P., Han, Z., and Song, M. (2022). El-rec: Enhanced user and news interaction for news recommendation. In 8th International Conference on Cloud Computing and Intelligent Systems, pages 355–359. IEEE.
Publicado
08/09/2026
Como Citar
VELOSO, Bráulio M.; FERREIRA, Anderson A..
Integrating Stochastic Models into News Recommender Systems: A Comparative Study with Hybrid Approaches. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 41. , 2026, São Carlos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 113-126.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2026.249152.
