{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T05:56:17Z","timestamp":1785304577276,"version":"3.55.0"},"reference-count":49,"publisher":"Elsevier BV","issue":"7","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing & Management"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.ipm.2026.104786","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T21:35:50Z","timestamp":1776116150000},"page":"104786","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"PA","title":["Disentangled graph recommendation via dynamic long and short-term intent modeling"],"prefix":"10.1016","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8940-9560","authenticated-orcid":false,"given":"Jian","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianrong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ipm.2026.104786_bib0001","article-title":"A survey of sequential recommendation systems: techniques, evaluation, and future directions","volume":"64","author":"Boka","year":"2024","journal-title":"Information Systems"},{"issue":"3","key":"10.1016\/j.ipm.2026.104786_bib0002","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3560487","article-title":"User cold-start recommendation via inductive heterogeneous graph neural network","volume":"41","author":"Cai","year":"2023","journal-title":"ACM Transactions on Information Systems"},{"key":"10.1016\/j.ipm.2026.104786_bib0003","unstructured":"Cai, X., Huang, C., Xia, L., & Ren, X. (2023b). LightGCL: Simple yet effective graph contrastive learning for recommendation. arXiv preprint arXiv: 2302.08191."},{"key":"10.1016\/j.ipm.2026.104786_bib0004","series-title":"Proceedings of the 47th international ACM SIGIR conference on research and development in information retrieval","first-page":"1274","article-title":"Sigformer: Sign-aware graph transformer for recommendation","author":"Chen","year":"2024"},{"issue":"2","key":"10.1016\/j.ipm.2026.104786_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103997","article-title":"Let long-term interests talk: An disentangled learning model for recommendation based on short-term interests generation","volume":"62","author":"Duan","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104786_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107176","article-title":"A novel session-based recommendation system using capsule graph neural network","volume":"185","author":"El Alaoui","year":"2025","journal-title":"Neural Networks"},{"issue":"1","key":"10.1016\/j.ipm.2026.104786_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103896","article-title":"Fusing temporal and semantic dependencies for session-based recommendation","volume":"62","author":"Fu","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104786_bib0008","series-title":"Proceedings of the ACM web conference 2024","first-page":"3297","article-title":"Efficient noise-decoupling for multi-behavior sequential recommendation","author":"Han","year":"2024"},{"key":"10.1016\/j.ipm.2026.104786_bib0009","series-title":"Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval","first-page":"639","article-title":"LightGCN: Simplifying and powering graph convolution network for recommendation","author":"He","year":"2020"},{"issue":"2","key":"10.1016\/j.ipm.2026.104786_bib0010","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3700890","article-title":"A survey on intent-aware recommender systems","volume":"3","author":"Jannach","year":"2024","journal-title":"ACM Transactions on Recommender Systems"},{"key":"10.1016\/j.ipm.2026.104786_bib0011","series-title":"Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining","first-page":"2020","article-title":"Dual channel hypergraph collaborative filtering","author":"Ji","year":"2020"},{"key":"10.1016\/j.ipm.2026.104786_bib0012","series-title":"Proceedings of the 46th international ACM SIGIR conference on research and development in information retrieval","first-page":"1680","article-title":"Graph transformer for recommendation","author":"Li","year":"2023"},{"key":"10.1016\/j.ipm.2026.104786_bib0013","series-title":"Proceedings of the 29th ACM SIGKDD conference on knowledge discovery and data mining","first-page":"1258","article-title":"Text is all you need: Learning language representations for sequential recommendation","author":"Li","year":"2023"},{"key":"10.1016\/j.ipm.2026.104786_bib0014","series-title":"Proceedings of the 2018 world wide web conference","first-page":"689","article-title":"Variational autoencoders for collaborative filtering","author":"Liang","year":"2018"},{"issue":"3","key":"10.1016\/j.ipm.2026.104786_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103680","article-title":"Integrating user short-term intentions and long-term preferences in heterogeneous hypergraph networks for sequential recommendation","volume":"61","author":"Liu","year":"2024","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104786_bib0016","doi-asserted-by":"crossref","first-page":"7149","DOI":"10.1109\/TMM.2022.3217449","article-title":"Disentangled multimodal representation learning for recommendation","volume":"25","author":"Liu","year":"2022","journal-title":"IEEE Transactions on Multimedia"},{"issue":"6","key":"10.1016\/j.ipm.2026.104786_bib0017","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3687481","article-title":"Cluster-based graph collaborative filtering","volume":"42","author":"Liu","year":"2024","journal-title":"ACM Transactions on Information Systems"},{"key":"10.1016\/j.ipm.2026.104786_bib0018","series-title":"Proceedings of the 30th ACM SIGKDD conference on knowledge discovery and data mining","first-page":"6566","article-title":"Multimodal pretraining, adaptation, and generation for recommendation: A survey","author":"Liu","year":"2024"},{"key":"10.1016\/j.ipm.2026.104786_bib0019","series-title":"Proceedings of the ACM web conference 2024","first-page":"334","article-title":"User distribution mapping modelling with collaborative filtering for cross domain recommendation","author":"Liu","year":"2024"},{"issue":"7","key":"10.1016\/j.ipm.2026.104786_bib0020","first-page":"1","article-title":"LMACL: Improving graph collaborative filtering with learnable model augmentation contrastive learning","volume":"18","author":"Liu","year":"2024","journal-title":"ACM Transactions on Knowledge Discovery from Data"},{"key":"10.1016\/j.ipm.2026.104786_bib0021","series-title":"Proceedings of the 47th international ACM SIGIR conference on research and development in information retrieval","first-page":"1609","article-title":"SelfGNN: Self-supervised graph neural networks for sequential recommendation","author":"Liu","year":"2024"},{"key":"10.1016\/j.ipm.2026.104786_bib0022","first-page":"188","article-title":"Learning disentangled representations for recommendation","volume":"32","author":"Ma","year":"2019","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.ipm.2026.104786_bib0023","series-title":"Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP)","first-page":"188","article-title":"Justifying recommendations using distantly-labeled reviews and fine-grained aspects","author":"Ni","year":"2019"},{"key":"10.1016\/j.ipm.2026.104786_bib0024","series-title":"Proceedings of the ACM web conference 2024","first-page":"3464","article-title":"Representation learning with large language models for recommendation","author":"Ren","year":"2024"},{"key":"10.1016\/j.ipm.2026.104786_bib0025","series-title":"Proceedings of the 46th international ACM SIGIR conference on research and development in information retrieval","first-page":"1137","article-title":"Disentangled contrastive collaborative filtering","author":"Ren","year":"2023"},{"key":"10.1016\/j.ipm.2026.104786_bib0026","unstructured":"Rendle, S., Freudenthaler, C., Gantner, Z., & Schmidt-Thieme, L. (2012). BPR: Bayesian personalized ranking from implicit feedback. arXiv preprint arXiv: 1205.2618."},{"key":"10.1016\/j.ipm.2026.104786_bib0027","first-page":"1915","article-title":"Dynamic routing between capsules","volume":"30","author":"Sabour","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.ipm.2026.104786_bib0028","article-title":"Intent-guided heterogeneous graph contrastive learning for recommendation","volume":"62","author":"Sang","year":"2025","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"6","key":"10.1016\/j.ipm.2026.104786_bib0029","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104231","article-title":"FiclRec: Frequency enhanced intent contrastive learning for sequential recommendation","volume":"62","author":"Su","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104786_bib0030","first-page":"2640","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.ipm.2026.104786_bib0031","first-page":"4214","article-title":"Hypergraph collaborative filtering with adaptive augmentation of graph data for recommendation","author":"Wang","year":"2025","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.ipm.2026.104786_bib0032","first-page":"740","article-title":"HGREC: Group recommendation with hypergraph convolutional networks","author":"Wang","year":"2024","journal-title":"IEEE Transactions on Computational Social Systems"},{"key":"10.1016\/j.ipm.2026.104786_bib0033","series-title":"Proceedings of the 17th ACM international conference on web search and data mining","first-page":"740","article-title":"Dynamic sparse learning: A novel paradigm for efficient recommendation","author":"Wang","year":"2024"},{"key":"10.1016\/j.ipm.2026.104786_bib0034","series-title":"Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval","first-page":"1001","article-title":"Disentangled graph collaborative filtering","author":"Wang","year":"2020"},{"key":"10.1016\/j.ipm.2026.104786_bib0035","series-title":"Proceedings of the 17th ACM international conference on web search and data mining","first-page":"806","article-title":"LLMREC: Large language models with graph augmentation for recommendation","author":"Wei","year":"2024"},{"key":"10.1016\/j.ipm.2026.104786_bib0036","series-title":"Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval","first-page":"726","article-title":"Self-supervised graph learning for recommendation","author":"Wu","year":"2021"},{"key":"10.1016\/j.ipm.2026.104786_bib0037","series-title":"Proceedings of the ACM web conference 2024","first-page":"3566","article-title":"Could small language models serve as recommenders? Towards data-centric cold-start recommendation","author":"Wu","year":"2024"},{"key":"10.1016\/j.ipm.2026.104786_bib0038","series-title":"Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval","first-page":"70","article-title":"Hypergraph contrastive collaborative filtering","author":"Xia","year":"2022"},{"key":"10.1016\/j.ipm.2026.104786_bib0039","series-title":"Proceedings of the fifteenth ACM international conference on web search and data mining","first-page":"1168","article-title":"Long short-term temporal meta-learning in online recommendation","author":"Xie","year":"2022"},{"issue":"2","key":"10.1016\/j.ipm.2026.104786_bib0040","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3677377","article-title":"Graph augmentation empowered contrastive learning for recommendation","volume":"43","author":"Xu","year":"2025","journal-title":"ACM Transactions on Information Systems"},{"issue":"2","key":"10.1016\/j.ipm.2026.104786_bib0041","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3618298","article-title":"Contrastive graph prompt-tuning for cross-domain recommendation","volume":"42","author":"Yi","year":"2023","journal-title":"ACM Transactions on Information Systems"},{"key":"10.1016\/j.ipm.2026.104786_bib0042","series-title":"Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval","first-page":"1294","article-title":"Are graph augmentations necessary? Simple graph contrastive learning for recommendation","author":"Yu","year":"2022"},{"key":"10.1016\/j.ipm.2026.104786_bib0043","unstructured":"Yue, Z., Rabhi,S., De Souza Pereira, M. G., Wang, D., & Oldridge, E. (2023). LlamaRec: Two-stage recommendation using large language models for ranking. arXiv preprint arXiv: 2311.02089."},{"issue":"7","key":"10.1016\/j.ipm.2026.104786_bib0044","doi-asserted-by":"crossref","first-page":"2942","DOI":"10.1109\/TKDE.2024.3361482","article-title":"Denoising item graph with disentangled learning for recommendation","volume":"36","author":"Zhang","year":"2024","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"5","key":"10.1016\/j.ipm.2026.104786_bib0045","first-page":"4741","article-title":"Dynamic graph neural networks for sequential recommendation","volume":"35","author":"Zhang","year":"2022","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.ipm.2026.104786_bib0046","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1162\/tacl_a_00632","article-title":"Benchmarking large language models for news summarization","volume":"12","author":"Zhang","year":"2024","journal-title":"Transactions of the Association for Computational Linguistics"},{"key":"10.1016\/j.ipm.2026.104786_bib0047","series-title":"Proceedings of the 47th international ACM SIGIR conference on research and development in information retrieval","first-page":"1253","article-title":"Exploring the individuality and collectivity of intents behind interactions for graph collaborative filtering","author":"Zhang","year":"2024"},{"key":"10.1016\/j.ipm.2026.104786_bib0048","series-title":"Proceedings of the 5th ACM international conference on multimedia in Asia workshops","first-page":"1","article-title":"MMRec: Simplifying multimodal recommendation","author":"Zhou","year":"2023"},{"key":"10.1016\/j.ipm.2026.104786_bib0049","doi-asserted-by":"crossref","first-page":"7543","DOI":"10.1109\/TMM.2024.3369875","article-title":"Disentangled graph variational auto-encoder for multimodal recommendation with interpretability","volume":"26","author":"Zhou","year":"2024","journal-title":"IEEE Transactions on Multimedia"}],"container-title":["Information Processing & Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001779?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001779?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T11:30:33Z","timestamp":1781955033000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306457326001779"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":49,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["S0306457326001779"],"URL":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104786","relation":{},"ISSN":["0306-4573"],"issn-type":[{"value":"0306-4573","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Disentangled graph recommendation via dynamic long and short-term intent modeling","name":"articletitle","label":"Article Title"},{"value":"Information Processing & Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104786","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104786"}}