{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T11:24:47Z","timestamp":1772277887642,"version":"3.50.1"},"reference-count":42,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.eswa.2025.130949","type":"journal-article","created":{"date-parts":[[2025,12,25]],"date-time":"2025-12-25T07:18:52Z","timestamp":1766647132000},"page":"130949","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Multi-cluster division fine-grained heterogeneous graph contrastive learning for multi-behavior recommendation"],"prefix":"10.1016","volume":"306","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-5470-6880","authenticated-orcid":false,"given":"Shuhui","family":"Shan","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4727-6781","authenticated-orcid":false,"given":"Chunhui","family":"Han","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0839-8773","authenticated-orcid":false,"given":"Wei","family":"Zhou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7999-417X","authenticated-orcid":false,"given":"Guanghui","family":"Sun","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6561-560X","authenticated-orcid":false,"given":"Junhao","family":"Wen","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2025.130949_bib0001","series-title":"Proceedings of the ACM recsys 2010 workshop on user-centric evaluation of recommender systems and their interfaces (UCERSTI), Barcelona, Spain","first-page":"26","article-title":"Information overload and usage of recommendations","author":"Aljukhadar","year":"2010"},{"key":"10.1016\/j.eswa.2025.130949_bib0002","first-page":"41","article-title":"Multi-task feature learning","volume":"19","author":"Argyriou","year":"2006","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.eswa.2025.130949_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107760","article-title":"Neighborhood structure enhancement and denoising method for multi-behavior recommendation","volume":"191","author":"Cai","year":"2025","journal-title":"Neural Networks"},{"key":"10.1016\/j.eswa.2025.130949_bib0004","series-title":"Proceedings of the 14th ACM international conference on web search and data mining","first-page":"635","article-title":"Bipartite graph embedding via mutual information maximization","author":"Cao","year":"2021"},{"key":"10.1016\/j.eswa.2025.130949_bib0005","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"3958","article-title":"Graph heterogeneous multi-relational recommendation","volume":"vol. 35","author":"Chen","year":"2021"},{"key":"10.1016\/j.eswa.2025.130949_bib0006","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"19","article-title":"Efficient heterogeneous collaborative filtering without negative sampling for recommendation","volume":"vol. 34","author":"Chen","year":"2020"},{"key":"10.1016\/j.eswa.2025.130949_bib0007","series-title":"Proceedings of the fourth ACM conference on recommender systems","first-page":"293","article-title":"The youtube video recommendation system","author":"Davidson","year":"2010"},{"key":"10.1016\/j.eswa.2025.130949_bib0008","series-title":"2019\u202fIEEE 35th international conference on data engineering (ICDE)","first-page":"1554","article-title":"Neural multi-task recommendation from multi-behavior data","author":"Gao","year":"2019"},{"key":"10.1016\/j.eswa.2025.130949_bib0009","series-title":"Proceedings of the thirteenth international conference on artificial intelligence and statistics","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"Glorot","year":"2010"},{"key":"10.1016\/j.eswa.2025.130949_bib0010","series-title":"International joint conference on artificial intelligence","first-page":"2052","article-title":"Self-supervised graph neural networks for multi-behavior recommendation","author":"Gu","year":"2022"},{"key":"10.1016\/j.eswa.2025.130949_bib0011","series-title":"Proceedings of the 26th international joint conference on artificial intelligence","first-page":"1725","article-title":"DeepFM: A factorization-machine based neural network for CTR prediction","author":"Guo","year":"2017"},{"issue":"8","key":"10.1016\/j.eswa.2025.130949_bib0012","doi-asserted-by":"crossref","first-page":"3549","DOI":"10.1109\/TKDE.2020.3028705","article-title":"A survey on knowledge graph-based recommender systems","volume":"34","author":"Guo","year":"2020","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.eswa.2025.130949_bib0013","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"},{"key":"10.1016\/j.eswa.2025.130949_bib0014","series-title":"Proceedings of the 26th international conference on world wide web","first-page":"173","article-title":"Neural collaborative filtering","author":"He","year":"2017"},{"key":"10.1016\/j.eswa.2025.130949_bib0015","series-title":"Proceedings of the web conference 2020","first-page":"2704","article-title":"Heterogeneous graph transformer","author":"Hu","year":"2020"},{"key":"10.1016\/j.eswa.2025.130949_bib0016","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"4115","article-title":"Knowledge-aware coupled graph neural network for social recommendation","volume":"vol. 35","author":"Huang","year":"2021"},{"key":"10.1016\/j.eswa.2025.130949_bib0017","series-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision","first-page":"2785","article-title":"Boosting contrastive self-supervised learning with false negative cancellation","author":"Huynh","year":"2022"},{"key":"10.1016\/j.eswa.2025.130949_bib0018","series-title":"Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval","first-page":"659","article-title":"Multi-behavior recommendation with graph convolutional networks","author":"Jin","year":"2020"},{"issue":"8","key":"10.1016\/j.eswa.2025.130949_bib0019","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/MC.2009.263","article-title":"Matrix factorization techniques for recommender systems","volume":"42","author":"Koren","year":"2009","journal-title":"Computer"},{"key":"10.1016\/j.eswa.2025.130949_bib0020","series-title":"Proceedings of the 24th ACM international on conference on information and knowledge management","first-page":"811","article-title":"Deep collaborative filtering via marginalized denoising auto-encoder","author":"Li","year":"2015"},{"key":"10.1016\/j.eswa.2025.130949_bib0021","series-title":"Proceedings of the ACM web conference 2022","first-page":"2320","article-title":"Improving graph collaborative filtering with neighborhood-enriched contrastive learning","author":"Lin","year":"2022"},{"key":"10.1016\/j.eswa.2025.130949_bib0022","series-title":"Proceedings of the 31st ACM international conference on information & knowledge management","first-page":"1379","article-title":"Dual-task learning for multi-behavior sequential recommendation","author":"Luo","year":"2022"},{"key":"10.1016\/j.eswa.2025.130949_bib0023","series-title":"Proceedings of the twenty-fifth conference on uncertainty in artificial intelligence","first-page":"452","article-title":"BPR: Bayesian personalized ranking from implicit feedback","author":"Rendle","year":"2009"},{"key":"10.1016\/j.eswa.2025.130949_bib0024","series-title":"Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval","first-page":"165","article-title":"Neural graph collaborative filtering","author":"Wang","year":"2019"},{"key":"10.1016\/j.eswa.2025.130949_bib0025","series-title":"Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining","first-page":"1726","article-title":"Self-supervised heterogeneous graph neural network with co-contrastive learning","author":"Wang","year":"2021"},{"key":"10.1016\/j.eswa.2025.130949_bib0026","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.eswa.2025.130949_bib0027","series-title":"Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval","first-page":"235","article-title":"A neural influence diffusion model for social recommendation","author":"Wu","year":"2019"},{"issue":"5","key":"10.1016\/j.eswa.2025.130949_bib0028","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3535101","article-title":"Graph neural networks in recommender systems: A survey","volume":"55","author":"Wu","year":"2022","journal-title":"ACM Computing Surveys"},{"key":"10.1016\/j.eswa.2025.130949_bib0029","series-title":"International conference on database systems for advanced applications","first-page":"166","article-title":"Multi-view multi-behavior contrastive learning in recommendation","author":"Wu","year":"2022"},{"key":"10.1016\/j.eswa.2025.130949_bib0030","series-title":"Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval","first-page":"2397","article-title":"Multiplex behavioral relation learning for recommendation via memory augmented transformer network","author":"Xia","year":"2020"},{"key":"10.1016\/j.eswa.2025.130949_bib0031","series-title":"Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval","first-page":"757","article-title":"Graph meta network for multi-behavior recommendation","author":"Xia","year":"2021"},{"key":"10.1016\/j.eswa.2025.130949_bib0032","series-title":"2021\u202fIEEE 37th international conference on data engineering (ICDE)","first-page":"2464","article-title":"Explore user neighborhood for real-time e-commerce recommendation","author":"Xie","year":"2021"},{"key":"10.1016\/j.eswa.2025.130949_bib0033","series-title":"Proceedings of the 46th international ACM SIGIR conference on research and development in information retrieval","first-page":"496","article-title":"Multi-behavior self-supervised learning for recommendation","author":"Xu","year":"2023"},{"key":"10.1016\/j.eswa.2025.130949_bib0034","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"7370","article-title":"Graph convolutional networks for text classification","volume":"vol. 33","author":"Yao","year":"2019"},{"key":"10.1016\/j.eswa.2025.130949_bib0035","series-title":"Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining","first-page":"974","article-title":"Graph convolutional neural networks for web-scale recommender systems","author":"Ying","year":"2018"},{"key":"10.1016\/j.eswa.2025.130949_bib0036","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.eswa.2025.130949_bib0037","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.129618","article-title":"Multi-behavioral recommendation algorithm based on decoupled graph convolution","volume":"298","author":"Yu","year":"2026","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2025.130949_bib0038","series-title":"Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval","first-page":"1642","article-title":"Multi-behavior sequential transformer recommender","author":"Yuan","year":"2022"},{"key":"10.1016\/j.eswa.2025.130949_bib0039","series-title":"Proceedings of the 48th international ACM SIGIR conference on research and development in information retrieval","first-page":"1985","article-title":"Unveiling contrastive learning\u2019s capability of neighborhood aggregation for collaborative filtering","author":"Zhang","year":"2025"},{"key":"10.1016\/j.eswa.2025.130949_bib0040","series-title":"Proceedings of the 2018 world wide web conference","first-page":"167","article-title":"DRN: A deep reinforcement learning framework for news recommendation","author":"Zheng","year":"2018"},{"key":"10.1016\/j.eswa.2025.130949_bib0041","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.aiopen.2021.01.001","article-title":"Graph neural networks: A review of methods and applications","volume":"1","author":"Zhou","year":"2020","journal-title":"AI Open"},{"key":"10.1016\/j.eswa.2025.130949_bib0042","series-title":"Proceedings of the web conference 2021","first-page":"2069","article-title":"Graph contrastive learning with adaptive augmentation","author":"Zhu","year":"2021"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417425045646?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417425045646?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:48:10Z","timestamp":1772264890000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417425045646"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":42,"alternative-id":["S0957417425045646"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2025.130949","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Multi-cluster division fine-grained heterogeneous graph contrastive learning for multi-behavior recommendation","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2025.130949","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"130949"}}