{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T04:09:12Z","timestamp":1768450152351,"version":"3.49.0"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T00:00:00Z","timestamp":1745193600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T00:00:00Z","timestamp":1745193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2021MF099, ZR2022MF334"],"award-info":[{"award-number":["ZR2021MF099, ZR2022MF334"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shandong Province Teaching Reform Research Project","award":["M2021130, M2022245, Z2022202"],"award-info":[{"award-number":["M2021130, M2022245, Z2022202"]}]},{"name":"Shandong Province High Quality Professional Degree Teaching Case Library Construction Project","award":["SDYAL2022155"],"award-info":[{"award-number":["SDYAL2022155"]}]},{"name":"2023 Jinan City School Integration Development Strategy Project:Research and demonstration of a federated learning open platform for e-commerce recommendation","award":["JNSX2023064"],"award-info":[{"award-number":["JNSX2023064"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1007\/s10489-024-06140-3","type":"journal-article","created":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T12:54:30Z","timestamp":1745240070000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Dual-channel context-aware contrastive learning graph neural networks for session-based recommendation"],"prefix":"10.1007","volume":"55","author":[{"given":"Jiawei","family":"Cao","sequence":"first","affiliation":[]},{"given":"Yumin","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Jiahui","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7104-0331","authenticated-orcid":false,"given":"Weihua","family":"Yuan","sequence":"additional","affiliation":[]},{"given":"Xuanfeng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Zhijun","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,21]]},"reference":[{"key":"6140_CR1","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/MC.2009.263","volume":"42","author":"Y Koren","year":"2009","unstructured":"Koren Y, Bell R, Volinsky C (2009) Matrix factorization techniques for recommender systems. Computer 42:30\u201337. https:\/\/doi.org\/10.1109\/MC.2009.263","journal-title":"Computer"},{"key":"6140_CR2","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.1109\/TPAMI.2016.2605085","volume":"39","author":"B Yang","year":"2017","unstructured":"Yang B, Lei Y, Liu J, Li W (2017) Social collaborative filtering by trust. IEEE Trans Pattern Anal Mach Intell 39:1633\u20131647. https:\/\/doi.org\/10.1109\/TPAMI.2016.2605085","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6140_CR3","doi-asserted-by":"crossref","unstructured":"Wang X, He X, Wang M, Feng F, Chua T (2019) Neural graph collaborative filtering. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 165\u2013174","DOI":"10.1145\/3331184.3331267"},{"key":"6140_CR4","doi-asserted-by":"crossref","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, pp 811\u2013820","DOI":"10.1145\/1772690.1772773"},{"key":"6140_CR5","doi-asserted-by":"crossref","unstructured":"Li J, Ren P, Chen Z, Ren Z, Lian T, Ma J (2017) Neural attentive session-based recommendation. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, pp 1419\u20131428","DOI":"10.1145\/3132847.3132926"},{"key":"6140_CR6","doi-asserted-by":"crossref","unstructured":"Wu S, Tang Y, Zhu Y, Wang L, Xie X, Tan T (2019) Session-based recommendation with graph neural networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, no. 01, pp 346\u2013353","DOI":"10.1609\/aaai.v33i01.3301346"},{"key":"6140_CR7","doi-asserted-by":"crossref","unstructured":"Wang Z, Wei W, Cong G, Li X, Mao X, Qiu M (2020) Global context enhanced graph neural networks for session-based recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 169\u2013178","DOI":"10.1145\/3397271.3401142"},{"key":"6140_CR8","doi-asserted-by":"crossref","unstructured":"Xia X, Yin H, Yu J, Shao Y, Cui L (2021) Self-supervised graph co-training for session-based recommendation. In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, pp 2180\u20132190","DOI":"10.1145\/3459637.3482388"},{"key":"6140_CR9","first-page":"3940","volume":"19","author":"C Xu","year":"2019","unstructured":"Xu C, Zhao P, Liu Y, Sheng VS, Xu J, Zhuang F, Fang J, Zhou X (2019) Graph contextualized self-attention network for session-based recommendation. IJCAI 19:3940\u20133946","journal-title":"IJCAI"},{"key":"6140_CR10","doi-asserted-by":"crossref","unstructured":"Liu Q, Zeng Y, Mokhosi R, Zhang H (2018) STAMP: short-term attention\/memory priority model for session-based recommendation. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp 1831\u20131839","DOI":"10.1145\/3219819.3219950"},{"key":"6140_CR11","doi-asserted-by":"crossref","unstructured":"Hidasi B, Karatzoglou A (2018) Recurrent neural networks with top-k gains for session-based recommendations. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management, pp 843\u2013852","DOI":"10.1145\/3269206.3271761"},{"key":"6140_CR12","doi-asserted-by":"crossref","unstructured":"Guo W, Wang S, Lu W, Wu H, Zhang Q, Shao Z (2021) Sequential dependency enhanced graph neural networks for session-based recommendations. In: 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA), pp 1\u201310","DOI":"10.1109\/DSAA53316.2021.9564224"},{"key":"6140_CR13","doi-asserted-by":"crossref","unstructured":"Wang H, Zeng Y, Chen J, Han N, Chen H (2023) Interval-enhanced graph transformer solution for session-based recommendation. In: Expert Systems with Applications, vol. 213, no. 118970","DOI":"10.1016\/j.eswa.2022.118970"},{"key":"6140_CR14","doi-asserted-by":"crossref","unstructured":"Guo Q, Sun Z, Zhang J, Theng YL (2020) An attentional recurrent neural network for personalized next location recommendation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 01, pp 83\u201390","DOI":"10.1609\/aaai.v34i01.5337"},{"key":"6140_CR15","doi-asserted-by":"crossref","unstructured":"Chang J, Gao C, Zheng Y, Hui Y, Niu Y, Song Y, Li Y (2021) Sequential recommendation with graph neural networks. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 378\u2013387","DOI":"10.1145\/3404835.3462968"},{"key":"6140_CR16","doi-asserted-by":"crossref","unstructured":"Zhu X, Tang G, Wang P, Li C, Guo J, Dietze S (2023) Dynamic global structure enhanced multi-channel graph neural network for session-based recommendation. In: Information Sciences, vol. 624, pp 324\u2013343","DOI":"10.1016\/j.ins.2022.10.025"},{"key":"6140_CR17","doi-asserted-by":"crossref","unstructured":"Wang C, Zhang M, Ma W (2020) Make it a chorus: knowledge-and time-aware item modeling for sequential recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 109\u2013118","DOI":"10.1145\/3397271.3401131"},{"key":"6140_CR18","doi-asserted-by":"crossref","unstructured":"Li X, Liu Y, Liu Z (2022) Time-aware hyperbolic graph attention network for session-based recommendation. In: 2022 IEEE International Conference on Big Data (Big Data). IEEE, pp 626\u2013635","DOI":"10.1109\/BigData55660.2022.10021075"},{"key":"6140_CR19","doi-asserted-by":"crossref","unstructured":"Xia X, Yin H, Yu J, Wang Q, Cui L, Zhang X (2021) Self-supervised hypergraph convolutional networks for session-based recommendation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 5, pp 4503\u20134511","DOI":"10.1609\/aaai.v35i5.16578"},{"key":"6140_CR20","doi-asserted-by":"crossref","unstructured":"Xie X, Sun F, Liu Z, Wu S, Gao J, Zhang J, Ding B, Cui B (2022) Contrastive learning for sequential recommendation. In: 2022 IEEE 38th international conference on data engineering (ICDE). IEEE, pp 1259\u20131273","DOI":"10.1109\/ICDE53745.2022.00099"},{"key":"6140_CR21","doi-asserted-by":"crossref","unstructured":"Lei C, Liu Y, Zhang L, Wang G, Tang H, Li H, Miao C (2021) Semi: A sequential multi-modal information transfer network for e-commerce micro-video recommendations. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pp 3161\u20133171","DOI":"10.1145\/3447548.3467189"},{"key":"6140_CR22","doi-asserted-by":"crossref","unstructured":"Li X, Sun A, Zhao M, Yu J, Zhu K, Jin D, Yu R (2023) Multi-intention oriented contrastive learning for sequential recommendation. In: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, pp 411\u2013419","DOI":"10.1145\/3539597.3570411"},{"key":"6140_CR23","doi-asserted-by":"crossref","unstructured":"He X, Deng K, Wang X, Li Y, Zhang Y, Wang M (2020) Lightgcn: simplifying and powering graph convolution network for recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 639\u2013648","DOI":"10.1145\/3397271.3401063"},{"key":"6140_CR24","unstructured":"Kipf TN, Welling M (2017) Semi-supervised classification with graph convolutional networks. In ICLR. OpenReview.net"},{"key":"6140_CR25","doi-asserted-by":"crossref","unstructured":"Zangerle E, Pichl M, Gassler W (2014) Nowplaying music dataset: extracting listening behavior from twitter. In: Proceedings of the first international workshop on internet-scale multimedia management, pp 21\u201326","DOI":"10.1145\/2661714.2661719"},{"key":"6140_CR26","doi-asserted-by":"crossref","unstructured":"Wang M, Ren P, Mei L, Chen Z, Ma J, de Rijke M (2019) A collaborative session-based recommendation approach with parallel memory modules. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp 345\u2013354","DOI":"10.1145\/3331184.3331210"},{"key":"6140_CR27","doi-asserted-by":"crossref","unstructured":"Wang J, Ding K, Zhu Z, Caverlee J (2021) Session-based recommendation with hypergraph attention networks. In: Proceedings of the 2021 SIAM International Conference on Data Mining (SDM), pp 82\u201390","DOI":"10.1137\/1.9781611976700.10"},{"issue":"8","key":"6140_CR28","first-page":"7870","volume":"35","author":"A Li","year":"2022","unstructured":"Li A, Cheng Z, Liu F, Gao Z, Guan W, Peng Y (2022) Disentangled graph neural networks for session-based recommendation. IEEE Trans Knowl Data Eng 35(8):7870\u20137882","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"6140_CR29","doi-asserted-by":"publisher","first-page":"26237","DOI":"10.1109\/ACCESS.2023.3254897","volume":"11","author":"Y Chen","year":"2023","unstructured":"Chen Y, Tang Y, Yuan Y (2023) Attention-enhanced graph neural networks with global context for session-based recommendation. IEEE Access 11:26237\u201326246","journal-title":"IEEE Access"},{"key":"6140_CR30","doi-asserted-by":"crossref","unstructured":"Schroff F, Kalenichenko D, Philbin J (2015) Facenet: A unified embedding for face recognition and clustering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 815\u2013823","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"6140_CR31","unstructured":"Liang S, Sun R, Li Y, Srikant R (2018) Understanding the loss surface of neural networks for binary classification. In: International Conference on Machine Learning, PMLR, pp 2835\u20132843"},{"key":"6140_CR32","unstructured":"Sohn K (2016) Improved deep metric learning with multi-class n-pair loss objective. In: Advances in Neural Information Processing Systems, vol. 29"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-06140-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-06140-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-06140-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T19:35:53Z","timestamp":1758310553000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-06140-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,21]]},"references-count":32,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,5]]}},"alternative-id":["6140"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-06140-3","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,21]]},"assertion":[{"value":"30 November 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 April 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"We declare that none of the authors have any financial or scientific conflicts of interest with regard to the research described in this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"All authors contributed to the study conception and design. Jiawei Cao: Conceptualization, Methodology, Software, Writing-Original draft preparation. Weihua Yuan: Data curation, Validation, Writing-Review and Editing; Yumin Fan, Tao Zhang, Jiahui Liu, Ruoqi Du: Supervision, Validation, Writing-Review and Editing; Xuanfeng Zhang, Zhijun Zhang: Writing-Reviewing and Editing. All authors read and approved the final manuscript.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"CRediT authorship contribution statement"}}],"article-number":"678"}}