{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T08:03:51Z","timestamp":1775030631585,"version":"3.50.1"},"reference-count":42,"publisher":"Elsevier BV","issue":"6","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"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","award":["62502059"],"award-info":[{"award-number":["62502059"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72301050"],"award-info":[{"award-number":["72301050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62272077"],"award-info":[{"award-number":["62272077"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007957","name":"Chongqing Municipal Education Commission","doi-asserted-by":"publisher","award":["KJZD-M202400604"],"award-info":[{"award-number":["KJZD-M202400604"]}],"id":[{"id":"10.13039\/501100007957","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007957","name":"Chongqing Municipal Education Commission","doi-asserted-by":"publisher","award":["KJZD-K202500304"],"award-info":[{"award-number":["KJZD-K202500304"]}],"id":[{"id":"10.13039\/501100007957","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007957","name":"Chongqing Municipal Education Commission","doi-asserted-by":"publisher","award":["KJQN-202500640"],"award-info":[{"award-number":["KJQN-202500640"]}],"id":[{"id":"10.13039\/501100007957","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing & Management"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.ipm.2026.104722","type":"journal-article","created":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T23:00:20Z","timestamp":1773529220000},"page":"104722","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Privacy-preserving heterogeneous graph representation learning for recommendation"],"prefix":"10.1016","volume":"63","author":[{"given":"Kun","family":"Wang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5247-043X","authenticated-orcid":false,"given":"Yong","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0772-7790","authenticated-orcid":false,"given":"Zhiqiang","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4761-132X","authenticated-orcid":false,"given":"Jiangzhou","family":"Deng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5471-5621","authenticated-orcid":false,"given":"Jingyuan","family":"Liu","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.ipm.2026.104722_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2025.107646","article-title":"Feature-decorrelation adaptive contrastive learning for knowledge-aware recommendation","author":"Cai","year":"2025","journal-title":"Neural Networks"},{"issue":"99","key":"10.1016\/j.ipm.2026.104722_bib0017","first-page":"1","article-title":"Secure federated matrix factorization","volume":"PP","author":"Chai","year":"2020","journal-title":"Intelligent Systems, IEEE"},{"key":"10.1016\/j.ipm.2026.104722_bib0009","series-title":"Proceedings of the sixteenth ACM international conference on web search and data mining","first-page":"544","article-title":"Heterogeneous graph contrastive learning for recommendation","author":"Chen","year":"2023"},{"issue":"3\u20134","key":"10.1016\/j.ipm.2026.104722_bib0028","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1561\/0400000042","article-title":"The algorithmic foundations of differential privacy","volume":"9","author":"Dwork","year":"2014","journal-title":"Foundations and trends\u00ae in theoretical computer science"},{"key":"10.1016\/j.ipm.2026.104722_bib0038","doi-asserted-by":"crossref","unstructured":"Fu, X., & King, I. (2023). FedHGN: a federated framework for heterogeneous graph neural networks. arXiv preprint arXiv:2305.09729.","DOI":"10.24963\/ijcai.2023\/412"},{"key":"10.1016\/j.ipm.2026.104722_bib0031","series-title":"Proceedings of the web conference","first-page":"2331","article-title":"Magnn: Metapath aggregated graph neural network for heterogeneous graph embedding","volume":"2020","author":"Fu","year":"2020"},{"key":"10.1016\/j.ipm.2026.104722_bib0001","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.ipm.2026.104722_bib0032","series-title":"Proceedings of the web conference 2020","first-page":"2704","article-title":"Heterogeneous graph transformer","author":"Hu","year":"2020"},{"issue":"1","key":"10.1016\/j.ipm.2026.104722_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103930","article-title":"LacGCL: lightweight message masking with linear attention and cross-view interaction graph contrastive learning for recommendation","volume":"62","author":"Jia","year":"2025","journal-title":"Information Processing & Management"},{"issue":"3","key":"10.1016\/j.ipm.2026.104722_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104075","article-title":"Exploiting diffusion-based structured learning for item interactions representations in multimodal recommender systems","volume":"62","author":"Khan","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104722_bib0034","article-title":"Mask diffusion-based contrastive learning for knowledge-aware recommendation","author":"Li","year":"2025","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.ipm.2026.104722_bib0025","doi-asserted-by":"crossref","first-page":"2936","DOI":"10.1109\/TIFS.2022.3198283","article-title":"Towards private learning on decentralized graphs with local differential privacy","volume":"17","author":"Lin","year":"2022","journal-title":"IEEE Transactions on Information Forensics and Security"},{"issue":"4","key":"10.1016\/j.ipm.2026.104722_bib0018","first-page":"1","article-title":"Federated social recommendation with graph neural network","volume":"13","author":"Liu","year":"2022","journal-title":"ACM Transactions on Intelligent Systems"},{"key":"10.1016\/j.ipm.2026.104722_bib0013","unstructured":"Liu, X., Zhang, J., Ren, C., Xu, S., Pan, Z., & Zhang, Z. (2024). Heterogeneous graph-based framework with disentangled representations learning for multi-target cross domain recommendation. arXiv preprint arXiv:2407.00909."},{"key":"10.1016\/j.ipm.2026.104722_bib0011","series-title":"Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval","first-page":"2029","article-title":"A heterogeneous graph neural model for cold-start recommendation","author":"Liu","year":"2020"},{"key":"10.1016\/j.ipm.2026.104722_bib0007","series-title":"Proceedings of the 30th ACM international conference on information & knowledge management","first-page":"1160","article-title":"Social recommendation with self-supervised metagraph informax network","author":"Long","year":"2021"},{"key":"10.1016\/j.ipm.2026.104722_bib0026","doi-asserted-by":"crossref","first-page":"1614","DOI":"10.1109\/TIFS.2023.3329971","article-title":"Privacy-enhanced graph neural network for decentralized local graphs","volume":"19","author":"Pei","year":"2023","journal-title":"IEEE Transactions on Information Forensics and Security"},{"key":"10.1016\/j.ipm.2026.104722_bib0036","doi-asserted-by":"crossref","first-page":"1614","DOI":"10.1109\/TIFS.2023.3329971","article-title":"Privacy-enhanced graph neural network for decentralized local graphs","volume":"19","author":"Pei","year":"2023","journal-title":"IEEE Transactions on Information Forensics and Security"},{"key":"10.1016\/j.ipm.2026.104722_bib0042","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.ipm.2026.104722_bib0015","series-title":"32nd USENIX Security Symposium (USENIX Security 23)","first-page":"3223","article-title":"{GAP}: Differentially private graph neural networks with aggregation perturbation","author":"Sajadmanesh","year":"2023"},{"key":"10.1016\/j.ipm.2026.104722_bib0005","first-page":"1","article-title":"Heterogeneous information network embedding for recommendation","author":"Shi","year":"2017","journal-title":"IEEE Transactions on Knowledge & Data Engineering"},{"issue":"5","key":"10.1016\/j.ipm.2026.104722_bib0019","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3653448","article-title":"Privacy-preserving cross-domain recommendation with federated graph learning","volume":"42","author":"Tian","year":"2024","journal-title":"ACM Transactions on Information Systems"},{"key":"10.1016\/j.ipm.2026.104722_bib0027","series-title":"Annual international conference on the theory and applications of cryptographic techniques","first-page":"24","article-title":"Fully homomorphic encryption over the integers","author":"Van Dijk","year":"2010"},{"issue":"2","key":"10.1016\/j.ipm.2026.104722_bib0040","doi-asserted-by":"crossref","first-page":"2525","DOI":"10.1007\/s10639-024-12895-6","article-title":"Roles of artificial intelligence experience, information redundancy, and familiarity in shaping active learning: insights from intelligent personal assistants","volume":"30","author":"Wang","year":"2025","journal-title":"Education and Information Technologies"},{"key":"10.1016\/j.ipm.2026.104722_bib0002","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.ipm.2026.104722_bib0030","series-title":"The world wide web conference","first-page":"2022","article-title":"Heterogeneous graph attention network","author":"Wang","year":"2019"},{"key":"10.1016\/j.ipm.2026.104722_bib0041","series-title":"International Conference on Artificial Intelligence and Statistics","article-title":"Subsampled r\u00e9nyi differential privacy and analytical moments accountant","author":"Wang","year":"2019"},{"key":"10.1016\/j.ipm.2026.104722_bib0016","series-title":"2022 IEEE International Conference on Data Mining (ICDM)","first-page":"528","article-title":"Heterogeneous graph neural network for privacy-preserving recommendation","author":"Wei","year":"2022"},{"issue":"1","key":"10.1016\/j.ipm.2026.104722_bib0020","doi-asserted-by":"crossref","first-page":"3091","DOI":"10.1038\/s41467-022-30714-9","article-title":"A federated graph neural network framework for privacy-preserving personalization","volume":"13","author":"Wu","year":"2022","journal-title":"Nature Communications"},{"key":"10.1016\/j.ipm.2026.104722_bib0014","series-title":"2022 ieee symposium on security and privacy (sp)","first-page":"2005","article-title":"Linkteller: recovering private edges from graph neural networks via influence analysis","author":"Wu","year":"2022"},{"key":"10.1016\/j.ipm.2026.104722_bib0021","series-title":"Proceedings of the ACM Web Conference","first-page":"3919","article-title":"Federated heterogeneous graph neural network for privacy-preserving recommendation","author":"Yan","year":"2024"},{"issue":"6","key":"10.1016\/j.ipm.2026.104722_bib0006","first-page":"5935","article-title":"Heterogeneous graph representation learning with relation awareness","volume":"35","author":"Yu","year":"2022","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"1","key":"10.1016\/j.ipm.2026.104722_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103868","article-title":"Global and local hypergraph learning method with semantic enhancement for POI recommendation","volume":"62","author":"Zeng","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104722_bib0029","series-title":"Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining","first-page":"793","article-title":"Heterogeneous graph neural network","author":"Zhang","year":"2019"},{"key":"10.1016\/j.ipm.2026.104722_bib0023","series-title":"Proceedings of the web conference 2021","first-page":"3002","article-title":"Graph embedding for recommendation against attribute inference attacks","author":"Zhang","year":"2021"},{"key":"10.1016\/j.ipm.2026.104722_bib0039","doi-asserted-by":"crossref","unstructured":"Zhang, C., Long, G., Zhou, T., Yan, P., Zhang, Z., Zhang, C., & Yang, B. (2023). Dual personalization on federated recommendation. arXiv preprint arXiv:2301.08143.","DOI":"10.24963\/ijcai.2023\/507"},{"key":"10.1016\/j.ipm.2026.104722_bib0008","unstructured":"Zhang, H., Shen, C., Sun, X., Tan, J., Rong, Y., Piao, C., & Yi, L. (2024). Adaptive coordinators and prompts on heterogeneous graphs for cross-domain recommendations. arXiv preprint arXiv:2410.11719."},{"key":"10.1016\/j.ipm.2026.104722_bib0022","series-title":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","first-page":"4131","article-title":"Gpfedrec: graph-guided personalization for federated recommendation","author":"Zhang","year":"2024"},{"key":"10.1016\/j.ipm.2026.104722_bib0033","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2025.113056","article-title":"Multi-view self-supervised learning on heterogeneous graphs for recommendation","volume":"174","author":"Zhang","year":"2025","journal-title":"Applied Soft Computing"},{"issue":"1","key":"10.1016\/j.ipm.2026.104722_bib0003","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103956","article-title":"Multi-view graph contrastive representation learning for bundle recommendation","volume":"62","author":"Zhang","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104722_bib0037","doi-asserted-by":"crossref","DOI":"10.1109\/TCE.2024.3503652","article-title":"Privacy-preserving federated heterogeneous graph learning via Pseudo-metapath generation","author":"Zhang","year":"2024","journal-title":"IEEE Transactions on Consumer Electronics"},{"key":"10.1016\/j.ipm.2026.104722_bib0024","series-title":"Proceedings of the 32nd ACM International Conference on Information and Knowledge Management","first-page":"3494","article-title":"Decentralized graph neural network for privacy-preserving recommendation","author":"Zheng","year":"2023"}],"container-title":["Information Processing & Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001135?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326001135?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T05:32:27Z","timestamp":1775021547000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306457326001135"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":42,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["S0306457326001135"],"URL":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104722","relation":{},"ISSN":["0306-4573"],"issn-type":[{"value":"0306-4573","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Privacy-preserving heterogeneous graph representation learning for recommendation","name":"articletitle","label":"Article Title"},{"value":"Information Processing & Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104722","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":"104722"}}