{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T06:04:03Z","timestamp":1773036243257,"version":"3.50.1"},"reference-count":42,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"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":["61074135"],"award-info":[{"award-number":["61074135"]}],"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":["61303096"],"award-info":[{"award-number":["61303096"]}],"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":["71101086"],"award-info":[{"award-number":["71101086"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Data &amp; Knowledge Engineering"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.datak.2026.102556","type":"journal-article","created":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T16:50:08Z","timestamp":1767891008000},"page":"102556","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A BERT model and momentum contrastive learning based sequential recommendation method and its implementation"],"prefix":"10.1016","volume":"163","author":[{"given":"Mingjun","family":"Xin","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9701-1820","authenticated-orcid":false,"given":"Ze","family":"He","sequence":"additional","affiliation":[]},{"given":"Zhijun","family":"Xiao","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.datak.2026.102556_b1","doi-asserted-by":"crossref","unstructured":"Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme, Factorizing personalized markov chains for next-basket recommendation, in: Proceedings of the 19th International Conference on World Wide Web, 2010, pp. 811\u2013820.","DOI":"10.1145\/1772690.1772773"},{"key":"10.1016\/j.datak.2026.102556_b2","series-title":"Session-based recommendations with recurrent neural networks","author":"Hidasi","year":"2015"},{"issue":"1","key":"10.1016\/j.datak.2026.102556_b3","first-page":"261","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.datak.2026.102556_b4","series-title":"2018 IEEE International Conference on Data Mining","first-page":"197","article-title":"Self-attentive sequential recommendation","author":"Kang","year":"2018"},{"key":"10.1016\/j.datak.2026.102556_b5","series-title":"Improving language understanding by generative pre-training","author":"Radford","year":"2018"},{"key":"10.1016\/j.datak.2026.102556_b6","series-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018"},{"key":"10.1016\/j.datak.2026.102556_b7","unstructured":"Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, Ross Girshick, Momentum contrast for unsupervised visual representation learning, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 9729\u20139738."},{"key":"10.1016\/j.datak.2026.102556_b8","series-title":"Vip5: Towards multimodal foundation models for recommendation","author":"Geng","year":"2023"},{"key":"10.1016\/j.datak.2026.102556_b9","series-title":"Recommendation as instruction following: A large language model empowered recommendation approach","author":"Zhang","year":"2023"},{"key":"10.1016\/j.datak.2026.102556_b10","doi-asserted-by":"crossref","unstructured":"Lei Li, Yongfeng Zhang, Li Chen, Prompt distillation for efficient llm-based recommendation, in: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023, pp. 1348\u20131357.","DOI":"10.1145\/3583780.3615017"},{"key":"10.1016\/j.datak.2026.102556_b11","series-title":"Chat-rec: Towards interactive and explainable llms-augmented recommender system","author":"Gao","year":"2023"},{"key":"10.1016\/j.datak.2026.102556_b12","doi-asserted-by":"crossref","unstructured":"Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He, Tallrec: An effective and efficient tuning framework to align large language model with recommendation, in: Proceedings of the 17th ACM Conference on Recommender Systems, 2023, pp. 1007\u20131014.","DOI":"10.1145\/3604915.3608857"},{"key":"10.1016\/j.datak.2026.102556_b13","series-title":"On the sentence embeddings from pre-trained language models","author":"Li","year":"2020"},{"key":"10.1016\/j.datak.2026.102556_b14","doi-asserted-by":"crossref","unstructured":"Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen, Towards universal sequence representation learning for recommender systems, in: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022, pp. 585\u2013593.","DOI":"10.1145\/3534678.3539381"},{"key":"10.1016\/j.datak.2026.102556_b15","series-title":"WhiteningBERT: An easy unsupervised sentence embedding approach","author":"Huang","year":"2021"},{"key":"10.1016\/j.datak.2026.102556_b16","series-title":"Whitening sentence representations for better semantics and faster retrieval","author":"Su","year":"2021"},{"key":"10.1016\/j.datak.2026.102556_b17","series-title":"2022 IEEE 38th International Conference on Data Engineering","first-page":"1259","article-title":"Contrastive learning for sequential recommendation","author":"Xie","year":"2022"},{"key":"10.1016\/j.datak.2026.102556_b18","doi-asserted-by":"crossref","unstructured":"Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix Yu, Ting Chen, Aditya Menon, Lichan Hong, Ed H Chi, Steve Tjoa, Jieqi Kang, et al., Self-supervised learning for large-scale item recommendations, in: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021, pp. 4321\u20134330.","DOI":"10.1145\/3459637.3481952"},{"key":"10.1016\/j.datak.2026.102556_b19","series-title":"Contrastive self-supervised sequential recommendation with robust augmentation","author":"Liu","year":"2021"},{"key":"10.1016\/j.datak.2026.102556_b20","doi-asserted-by":"crossref","unstructured":"Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie, Self-supervised graph learning for recommendation, in: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021, pp. 726\u2013735.","DOI":"10.1145\/3404835.3462862"},{"key":"10.1016\/j.datak.2026.102556_b21","doi-asserted-by":"crossref","unstructured":"Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li, A review-aware graph contrastive learning framework for recommendation, in: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022, pp. 1283\u20131293.","DOI":"10.1145\/3477495.3531927"},{"key":"10.1016\/j.datak.2026.102556_b22","doi-asserted-by":"crossref","unstructured":"Chengfeng Xu, Pengpeng Zhao, Yanchi Liu, Jiajie Xu, Victor S Sheng S. Sheng, Zhiming Cui, Xiaofang Zhou, Hui Xiong, Recurrent convolutional neural network for sequential recommendation, in: The World Wide Web Conference, 2019, pp. 3398\u20133404.","DOI":"10.1145\/3308558.3313408"},{"issue":"2","key":"10.1016\/j.datak.2026.102556_b23","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1007\/s11280-022-01056-9","article-title":"Long short-term enhanced memory for sequential recommendation","volume":"26","author":"Duan","year":"2023","journal-title":"World Wide Web"},{"key":"10.1016\/j.datak.2026.102556_b24","doi-asserted-by":"crossref","unstructured":"Hongyang Gao, Zhengyang Wang, Shuiwang Ji, Large-scale learnable graph convolutional networks, in: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018, pp. 1416\u20131424.","DOI":"10.1145\/3219819.3219947"},{"key":"10.1016\/j.datak.2026.102556_b25","series-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016"},{"key":"10.1016\/j.datak.2026.102556_b26","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.neucom.2021.11.068","article-title":"Graph neural networks with global noise filtering for session-based recommendation","volume":"472","author":"Feng","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.datak.2026.102556_b27","doi-asserted-by":"crossref","unstructured":"Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V Chawla, Heterogeneous graph neural network, in: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019, pp. 793\u2013803.","DOI":"10.1145\/3292500.3330961"},{"key":"10.1016\/j.datak.2026.102556_b28","doi-asserted-by":"crossref","unstructured":"Chengxi Li, Yejing Wang, Qidong Liu, Xiangyu Zhao, Wanyu Wang, Yiqi Wang, Lixin Zou, Wenqi Fan, Qing Li, STRec: Sparse transformer for sequential recommendations, in: Proceedings of the 17th ACM Conference on Recommender Systems, 2023, pp. 101\u2013111.","DOI":"10.1145\/3604915.3608779"},{"key":"10.1016\/j.datak.2026.102556_b29","series-title":"Roberta: A robustly optimized bert pretraining approach","author":"Liu","year":"2019"},{"key":"10.1016\/j.datak.2026.102556_b30","series-title":"Tinybert: Distilling bert for natural language understanding","author":"Jiao","year":"2019"},{"issue":"2","key":"10.1016\/j.datak.2026.102556_b31","first-page":"3","article-title":"Lora: Low-rank adaptation of large language models","volume":"1","author":"Hu","year":"2022","journal-title":"ICLR"},{"key":"10.1016\/j.datak.2026.102556_b32","series-title":"Sentence-BERT: Sentence embeddings using siamese BERT-networks","author":"Reimers","year":"2019"},{"key":"10.1016\/j.datak.2026.102556_b33","series-title":"What do you learn from context? probing for sentence structure in contextualized word representations","author":"Tenney","year":"2019"},{"key":"10.1016\/j.datak.2026.102556_b34","series-title":"International Conference on Machine Learning","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","author":"Chen","year":"2020"},{"key":"10.1016\/j.datak.2026.102556_b35","doi-asserted-by":"crossref","unstructured":"Julian McAuley, Christopher Targett, Qinfeng Shi, Anton Van Den Hengel, Image-based recommendations on styles and substitutes, in: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015, pp. 43\u201352.","DOI":"10.1145\/2766462.2767755"},{"key":"10.1016\/j.datak.2026.102556_b36","doi-asserted-by":"crossref","unstructured":"Shaowei Wei, Zhengwei Wu, Xin Li, Qintong Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu, Leave no one behind: Online self-supervised self-distillation for sequential recommendation, in: Proceedings of the ACM Web Conference 2024, 2024, pp. 3767\u20133776.","DOI":"10.1145\/3589334.3645590"},{"key":"10.1016\/j.datak.2026.102556_b37","series-title":"BPR: Bayesian personalized ranking from implicit feedback","author":"Rendle","year":"2012"},{"key":"10.1016\/j.datak.2026.102556_b38","doi-asserted-by":"crossref","unstructured":"Jiaxi Tang, Ke Wang, Personalized top-n sequential recommendation via convolutional sequence embedding, in: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018, pp. 565\u2013573.","DOI":"10.1145\/3159652.3159656"},{"key":"10.1016\/j.datak.2026.102556_b39","doi-asserted-by":"crossref","unstructured":"Kun Zhou, Hui Wang, Wayne Xin Zhao, Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, Ji-Rong Wen, S3-rec: Self-supervised learning for sequential recommendation with mutual information maximization, in: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, 2020, pp. 1893\u20131902.","DOI":"10.1145\/3340531.3411954"},{"key":"10.1016\/j.datak.2026.102556_b40","doi-asserted-by":"crossref","unstructured":"Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, Peng Jiang, BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer, in: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019, pp. 1441\u20131450.","DOI":"10.1145\/3357384.3357895"},{"key":"10.1016\/j.datak.2026.102556_b41","doi-asserted-by":"crossref","unstructured":"Wayne Xin Zhao, Shanlei Mu, Yupeng Hou, Zihan Lin, Yushuo Chen, Xingyu Pan, Kaiyuan Li, Yujie Lu, Hui Wang, Changxin Tian, et al., Recbole: Towards a unified, comprehensive and efficient framework for recommendation algorithms, in: Proceedings of the 30th Acm International Conference on Information & Knowledge Management, 2021, pp. 4653\u20134664.","DOI":"10.1145\/3459637.3482016"},{"key":"10.1016\/j.datak.2026.102556_b42","article-title":"A method for stochastic optimization. Int. Conf. Learn","volume":"6","author":"Kingma","year":"2015","journal-title":"Represent. (ICLR)"}],"container-title":["Data &amp; Knowledge Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169023X26000030?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169023X26000030?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T05:05:25Z","timestamp":1773032725000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0169023X26000030"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":42,"alternative-id":["S0169023X26000030"],"URL":"https:\/\/doi.org\/10.1016\/j.datak.2026.102556","relation":{},"ISSN":["0169-023X"],"issn-type":[{"value":"0169-023X","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A BERT model and momentum contrastive learning based sequential recommendation method and its implementation","name":"articletitle","label":"Article Title"},{"value":"Data & Knowledge Engineering","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.datak.2026.102556","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"102556"}}