{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T21:28:11Z","timestamp":1783114091496,"version":"3.54.6"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T00:00:00Z","timestamp":1758499200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T00:00:00Z","timestamp":1758499200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Inf Syst"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1007\/s10844-025-00986-w","type":"journal-article","created":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T11:00:50Z","timestamp":1758538850000},"page":"829-855","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Fusion of diffusion models and intent learning in sequential recommendation"],"prefix":"10.1007","volume":"64","author":[{"given":"Jian","family":"Feng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyue","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,22]]},"reference":[{"key":"986_CR1","doi-asserted-by":"publisher","unstructured":"Cai, T., Zhang, Y., Li, K., et al. (2025). Feature-decorrelation adaptive contrastive learning for knowledge-aware recommendation. Neural Networks, 190, Article 107646. https:\/\/doi.org\/10.1016\/j.neunet.2025.107646","DOI":"10.1016\/j.neunet.2025.107646"},{"key":"986_CR2","doi-asserted-by":"publisher","unstructured":"Cen, Y., Zhang, J., Zou, X., et\u00a0al. (2020). Controllable multi-interest framework for recommendation. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, New York, p. 2942\u20132951, https:\/\/doi.org\/10.1145\/3394486.3403344","DOI":"10.1145\/3394486.3403344"},{"key":"986_CR3","doi-asserted-by":"publisher","unstructured":"Chen, J., Zou, G., Zhou, P., et\u00a0al. (2024). Sparse enhanced network: An adversarial generation method for robust augmentation in sequential recommendation. In: Proceedings of the AAAI Conference on Artificial Intelligence. AAAI Press, Hong Kong, pp. 8283\u20138291, https:\/\/doi.org\/10.1609\/aaai.v38i8.28669","DOI":"10.1609\/aaai.v38i8.28669"},{"key":"986_CR4","doi-asserted-by":"publisher","unstructured":"Chen, Y., Liu, Z., Li, J., et\u00a0al (2022) Intent contrastive learning for sequential recommendation. In: Proceedings of the ACM Web Conference 2022. Association for Computing Machinery, New York, p. 2172\u20132182, https:\/\/doi.org\/10.1145\/3485447.3512090","DOI":"10.1145\/3485447.3512090"},{"key":"986_CR5","doi-asserted-by":"publisher","unstructured":"Fan, X., Liu, Z., Lian, J., et\u00a0al (2021) Lighter and better: Low-rank decomposed self-attention networks for next-item recommendation. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, New York, pp. 1733\u20131737, https:\/\/doi.org\/10.1145\/3404835.3462978","DOI":"10.1145\/3404835.3462978"},{"key":"986_CR6","doi-asserted-by":"publisher","first-page":"485","DOI":"10.1007\/s10844-023-00825-w","volume":"62","author":"A Gao","year":"2024","unstructured":"Gao, A., Qin, J., Ma, C., et al. (2024). Bmdf-sr: bidirectional multi-sequence decoupling fusion method for sequential recommendation. Journal of Intelligent Information Systems, 62, 485\u2013507. https:\/\/doi.org\/10.1007\/s10844-023-00825-w","journal-title":"Journal of Intelligent Information Systems"},{"key":"986_CR7","doi-asserted-by":"publisher","unstructured":"Hatamizadeh, A., Tang, Y., Nath, V., et\u00a0al. (2021). Unetr: Transformers for 3d medical image segmentation. In: 2022 IEEE\/CVF Winter Conference on Applications of Computer Vision. IEEE, Piscataway, pp. 1748\u20131758, https:\/\/doi.org\/10.1109\/WACV51458.2022.00181","DOI":"10.1109\/WACV51458.2022.00181"},{"key":"986_CR8","unstructured":"Hidasi, B., Karatzoglou, A., Baltrunas, L., et\u00a0al. (2015). Session-based recommendations with recurrent neural networks, arXiv:1511.06939"},{"key":"986_CR9","doi-asserted-by":"publisher","unstructured":"Kang, W., & McAuley, J. (2018). Self-attentive sequential recommendation. In: 2018 IEEE International Conference on Data Mining (ICDM). IEEE, Piscataway, pp. 197\u2013206, https:\/\/doi.org\/10.1109\/ICDM.2018.00035","DOI":"10.1109\/ICDM.2018.00035"},{"key":"986_CR10","doi-asserted-by":"publisher","first-page":"5407","DOI":"10.1109\/TKDE.2025.3582767","volume":"37","author":"K Li","year":"2025","unstructured":"Li, K., Zhang, Y., Li, X., et al. (2025). Mask diffusion-based contrastive learning for knowledge-aware recommendation. IEEE Transactions on Knowledge and Data Engineering, 37, 5407\u20135419. https:\/\/doi.org\/10.1109\/TKDE.2025.3582767","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"986_CR11","doi-asserted-by":"publisher","unstructured":"Li, X., Sun, A., Zhao, M., et\u00a0al. (2023a)\/ Multi-intention oriented contrastive learning for sequential recommendation. In: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, New York, p. 411\u2013419, https:\/\/doi.org\/10.1145\/3539597.3570411","DOI":"10.1145\/3539597.3570411"},{"key":"986_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3631116","volume":"42","author":"Z Li","year":"2023","unstructured":"Li, Z., Sun, A., & Li, C. (2023). Diffurec: A diffusion model for sequential recommendation. ACM Transactions on Information Systems, 42, 1\u201328. https:\/\/doi.org\/10.1145\/3631116","journal-title":"ACM Transactions on Information Systems"},{"key":"986_CR13","doi-asserted-by":"publisher","unstructured":"Liu, Q., Wu, X., Wang, Y., et\u00a0al. (2025). Llm-esr: Large language models enhancement for long-tailed sequential recommendation. In: Proceedings of the 38th International Conference on Neural Information Processing Systems. Curran Associates Inc., Red Hook, pp. 26701\u201326727, https:\/\/doi.org\/10.5555\/3737916.3738755","DOI":"10.5555\/3737916.3738755"},{"key":"986_CR14","doi-asserted-by":"publisher","unstructured":"Liu, Y., Zhu, S., Xia, J., et\u00a0al. (2024). End-to-end learnable clustering for intent learning in recommendation. In: Advances in Neural Information Processing Systems. Association for Computing Machinery, New York, pp. 5913\u20135949, https:\/\/doi.org\/10.5555\/3737916.3738108","DOI":"10.5555\/3737916.3738108"},{"key":"986_CR15","doi-asserted-by":"publisher","unstructured":"Liu, Z., Li, X., Fan, Z., et\u00a0al. (2020). Basket recommendation with multi-intent translation graph neural network. In: 2020 IEEE International Conference on Big Data (Big Data). IEEE, Piscataway, pp. 728\u2013737, https:\/\/doi.org\/10.1109\/BigData50022.2020.9377917","DOI":"10.1109\/BigData50022.2020.9377917"},{"key":"986_CR16","doi-asserted-by":"publisher","unstructured":"Liu, Z., Fan, Z., Wang, Y., et\u00a0al. (2021). Augmenting sequential recommendation with pseudo-prior items via reversely pre-training transformer. In: Proceedings of the 44th international ACM SIGIR conference on Research and development in information retrieval. Association for Computing Machinery, New York, pp. 1608\u20131612, https:\/\/doi.org\/10.1145\/3404835.3463036","DOI":"10.1145\/3404835.3463036"},{"key":"986_CR17","doi-asserted-by":"publisher","unstructured":"Luo, H., Yu, Z., Xu, G., et\u00a0al. (2024). Diff-eisr: Diffusion enhanced intent modeling for sequential recommendation. In: International Conference on Intelligent Computing. Springer, Singapore, pp. 410\u2013420, https:\/\/doi.org\/10.1007\/978-981-96-9881-3_34","DOI":"10.1007\/978-981-96-9881-3_34"},{"key":"986_CR18","doi-asserted-by":"publisher","first-page":"1055","DOI":"10.1007\/s10844-025-00926-8","volume":"63","author":"Y Mo","year":"2025","unstructured":"Mo, Y., Liu, Y., Ye, C., et al. (2025). Adaptive multi-round retrieval with knowledge distillation for sequential recommendation. Journal of Intelligent Information Systems, 63, 1055\u20131077. https:\/\/doi.org\/10.1007\/s10844-025-00926-8","journal-title":"Journal of Intelligent Information Systems"},{"key":"986_CR19","doi-asserted-by":"publisher","unstructured":"Pan, Z., Cai, F., Ling, Y., et\u00a0al. (2020). An intent-guided collaborative machine for session-based recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, New York, p. 1833\u20131836, https:\/\/doi.org\/10.1145\/3397271.3401273","DOI":"10.1145\/3397271.3401273"},{"key":"986_CR20","doi-asserted-by":"publisher","unstructured":"Qin, X., Yuan, H., Zhao, P., et\u00a0al. (2024). Intent contrastive learning with cross subsequences for sequential recommendation. In: Proceedings of the 17th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, New York, p. 548\u2013556, https:\/\/doi.org\/10.1145\/3616855.3635773","DOI":"10.1145\/3616855.3635773"},{"key":"986_CR21","doi-asserted-by":"publisher","unstructured":"Rendle, S., Freudenthaler, C., Gantner, Z., et\u00a0al. (2009). Bpr: Bayesian personalized ranking from implicit feedback. In: Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence. AUAI Press, Arlington, p. 452\u2013461, https:\/\/doi.org\/10.5555\/1795114.1795167","DOI":"10.5555\/1795114.1795167"},{"key":"986_CR22","doi-asserted-by":"publisher","unstructured":"Rendle, S., Freudenthaler, C., & Schmidt-Thieme, L. (2010). Factorizing personalized markov chains for next-basket recommendation. In: Proceedings of the 19th International Conference on World Wide Web. Association for Computing Machinery, New York, pp. 811\u2013820, https:\/\/doi.org\/10.1145\/1772690.1772773","DOI":"10.1145\/1772690.1772773"},{"key":"986_CR23","doi-asserted-by":"publisher","unstructured":"Sun, F., Liu, J., Wu, J., et\u00a0al. (2019). Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer. In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, New York, pp. 1441\u20131450, https:\/\/doi.org\/10.1145\/3357384.3357895","DOI":"10.1145\/3357384.3357895"},{"key":"986_CR24","doi-asserted-by":"publisher","unstructured":"Tang, J., & Wang, K. (2018). Personalized top-n sequential recommendation via convolutional sequence embedding. In: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, New York, p. 565\u2013573, https:\/\/doi.org\/10.1145\/3159652.3159656","DOI":"10.1145\/3159652.3159656"},{"key":"986_CR25","doi-asserted-by":"publisher","unstructured":"Tanjim, M., Su, C., Benjamin, E., et\u00a0al. (2020). Attentive sequential models of latent intent for next item recommendation. In: Proceedings of The Web Conference 2020. Association for Computing Machinery, New York, pp. 2528\u20132534, https:\/\/doi.org\/10.1145\/3366423.3380002","DOI":"10.1145\/3366423.3380002"},{"key":"986_CR26","doi-asserted-by":"publisher","first-page":"171","DOI":"10.2478\/jaiscr-2024-0010","volume":"14","author":"H Vaghari","year":"2024","unstructured":"Vaghari, H., Aghdam, M., & Emami, H. (2024). Diarec: Dynamic intention-aware recommendation with attention-based context-aware item attributes modeling. Journal of Artificial Intelligence and Soft Computing Research, 14, 171\u2013189. https:\/\/doi.org\/10.2478\/jaiscr-2024-0010","journal-title":"Journal of Artificial Intelligence and Soft Computing Research"},{"key":"986_CR27","doi-asserted-by":"publisher","unstructured":"Vaghari, H., Aghdam, M., & Emami, H. (2025). Group attention for collaborative filtering with sequential feedback and context aware attributes. Scientific Reports, 15, 10050. https:\/\/doi.org\/10.1038\/s41598-025-94256-y","DOI":"10.1038\/s41598-025-94256-y"},{"key":"986_CR28","doi-asserted-by":"publisher","unstructured":"Vaghari, H., Aghdam, M., & Emami, H. (2025b). Han: Hierarchical attention network for learning latent context-aware user preferences with attribute awareness. IEEE Access 13, 49030\u201349049. https:\/\/doi.org\/10.1109\/ACCESS.2025.3551402","DOI":"10.1109\/ACCESS.2025.3551402"},{"key":"986_CR29","doi-asserted-by":"publisher","unstructured":"Wang, C., Ma, W., Chen, C., et\u00a0al (2023a) Sequential recommendation with multiple contrast signals. ACM Transactions on Information Systems 41, 1\u201327. https:\/\/doi.org\/10.1145\/3522673","DOI":"10.1145\/3522673"},{"key":"986_CR30","doi-asserted-by":"publisher","unstructured":"Wang, S., Hu, L., Wang, Y., et\u00a0al. (2019). Modeling multi-purpose sessions for next-item recommendations via mixture-channel purpose routing networks. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence. AAAI Press, Menlo Park, pp. 3771\u20133777, https:\/\/doi.org\/10.5555\/3367471.3367565","DOI":"10.5555\/3367471.3367565"},{"key":"986_CR31","doi-asserted-by":"publisher","unstructured":"Wang, W., Xu, Y., Feng, F., et\u00a0al. (2023b). Diffusion recommender model. In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, New York, p. 832\u2013841, https:\/\/doi.org\/10.1145\/3539618.3591663","DOI":"10.1145\/3539618.3591663"},{"key":"986_CR32","doi-asserted-by":"publisher","unstructured":"Wang, Y., Wang, X., Huang, X., et\u00a0al. (2023c). Intent-aware recommendation via disentangled graph contrastive learning. In: International Joint Conference on Artificial Intelligence. Morgan Kaufmann, San Francisco, pp. 2343\u20132351, https:\/\/doi.org\/10.24963\/ijcai.2023\/260","DOI":"10.24963\/ijcai.2023\/260"},{"key":"986_CR33","doi-asserted-by":"publisher","first-page":"745","DOI":"10.1007\/s10844-024-00915-3","volume":"63","author":"Y Wang","year":"2025","unstructured":"Wang, Y., Shi, X., & Zhao, X. (2025). Mllm4rec: multimodal information enhancing llm for sequential recommendation. Journal of Intelligent Information Systems, 63, 745\u2013761. https:\/\/doi.org\/10.1007\/s10844-024-00915-3","journal-title":"Journal of Intelligent Information Systems"},{"key":"986_CR34","doi-asserted-by":"publisher","unstructured":"Wu, Z., Wang, X., Chen, H., et\u00a0al. (2023). Diff4rec: Sequential recommendation with curriculum-scheduled diffusion augmentation. In: Proceedings of the 31st ACM International Conference on Multimedia. Association for Computing Machinery, New York, p. 9329\u20139335, https:\/\/doi.org\/10.1145\/3581783.3612709","DOI":"10.1145\/3581783.3612709"},{"key":"986_CR35","doi-asserted-by":"publisher","unstructured":"Xie, X., Sun, F., Liu, Z., et\u00a0al. (2022). Contrastive learning for sequential recommendation. In: 2022 IEEE 38th International Conference on Data Engineering. IEEE, Piscataway, pp. 1259\u20131273, https:\/\/doi.org\/10.1109\/ICDE53745.2022.00099","DOI":"10.1109\/ICDE53745.2022.00099"},{"key":"986_CR36","doi-asserted-by":"publisher","first-page":"11851","DOI":"10.1109\/JSTARS.2025.3563798","volume":"18","author":"Z Ying","year":"2025","unstructured":"Ying, Z., Ke, W., Zhai, Y., et al. (2025). Diffusar: Frequency domain-aware diffusion model for sar image generation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 11851\u201311866. https:\/\/doi.org\/10.1109\/JSTARS.2025.3563798","journal-title":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"},{"key":"986_CR37","doi-asserted-by":"publisher","unstructured":"You, D., & Kyumin, L. (2024) Context matters: Enhancing sequential recommendation with context-aware diffusion-based contrastive learning. In: 2024 IEEE International Conference on Big Data. IEEE, Piscataway, pp. 670\u2013679, https:\/\/doi.org\/10.1109\/BigData62323.2024.10826051","DOI":"10.1109\/BigData62323.2024.10826051"},{"key":"986_CR38","doi-asserted-by":"publisher","unstructured":"Zhao, J., Wen, Q., Sun, S., et al. (2025). Multi-view self-supervised learning on heterogeneous graphs for recommendation. Applied Soft Computing, 174, Article 113056. https:\/\/doi.org\/10.1016\/j.asoc.2025.113056","DOI":"10.1016\/j.asoc.2025.113056"},{"key":"986_CR39","doi-asserted-by":"publisher","unstructured":"Zhou, K., Wang, H., Zhao, W., et\u00a0al. (2020). S3-rec: Self-supervised learning for sequential recommendation with mutual information maximization. In: Proceedings of the 29th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, New York, p. 1893\u20131902, https:\/\/doi.org\/10.1145\/3340531.3411954","DOI":"10.1145\/3340531.3411954"}],"container-title":["Journal of Intelligent Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-025-00986-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10844-025-00986-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-025-00986-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T02:45:36Z","timestamp":1778035536000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10844-025-00986-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,22]]},"references-count":39,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["986"],"URL":"https:\/\/doi.org\/10.1007\/s10844-025-00986-w","relation":{},"ISSN":["0925-9902","1573-7675"],"issn-type":[{"value":"0925-9902","type":"print"},{"value":"1573-7675","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,22]]},"assertion":[{"value":"6 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 September 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 September 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}]}}