{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T07:29:04Z","timestamp":1780471744707,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":43,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T00:00:00Z","timestamp":1729468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Shandong Excellent Young Scientists Fund (Oversea)","award":["2022HWYQ-044"],"award-info":[{"award-number":["2022HWYQ-044"]}]},{"DOI":"10.13039\/https:\/\/doi.org\/10.13039\/501100010040","name":"Taishan Scholar Project of Shandong Province","doi-asserted-by":"publisher","award":["tsqn202306066"],"award-info":[{"award-number":["tsqn202306066"]}],"id":[{"id":"10.13039\/https:\/\/doi.org\/10.13039\/501100010040","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Program of New Twenty Policies for Universities of Jinan","award":["202333008"],"award-info":[{"award-number":["202333008"]}]},{"DOI":"10.13039\/https:\/\/doi.org\/10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62376130,62202270"],"award-info":[{"award-number":["62376130,62202270"]}],"id":[{"id":"10.13039\/https:\/\/doi.org\/10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Program of Innovation Improvement of Shandong","award":["2023TSGC0182"],"award-info":[{"award-number":["2023TSGC0182"]}]},{"name":"Shandong Provincial Natural Science Foundation","award":["ZR2022MF243"],"award-info":[{"award-number":["ZR2022MF243"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,21]]},"DOI":"10.1145\/3627673.3679699","type":"proceedings-article","created":{"date-parts":[[2024,10,20]],"date-time":"2024-10-20T19:34:21Z","timestamp":1729452861000},"page":"3042-3051","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Time-Series Representation Learning via Dual Reference Contrasting"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-2605-7236","authenticated-orcid":false,"given":"Rui","family":"Yu","sequence":"first","affiliation":[{"name":"Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences) &amp; Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan, Shandong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3948-4471","authenticated-orcid":false,"given":"Yongshun","family":"Gong","sequence":"additional","affiliation":[{"name":"School of Software, Shandong University, Jinan, Shandong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1133-9379","authenticated-orcid":false,"given":"Shoujin","family":"Wang","sequence":"additional","affiliation":[{"name":"Data Science Institute, University of Technology Sydney, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6870-5678","authenticated-orcid":false,"given":"Jiasheng","family":"Si","sequence":"additional","affiliation":[{"name":"Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8901-1472","authenticated-orcid":false,"given":"Xueping","family":"Peng","sequence":"additional","affiliation":[{"name":"Australian Artificial Intelligence Institute, University of Technology Sydney, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9125-8669","authenticated-orcid":false,"given":"Bing","family":"Xu","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1840-3540","authenticated-orcid":false,"given":"Wenpeng","family":"Lu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences) &amp; Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan, Shandong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,10,21]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proceedings of the 3rd International Workshop on Cyber-physical Systems for Smart Water Networks. 25--28","author":"Ahmed Chuadhry Mujeeb","unstructured":"Chuadhry Mujeeb Ahmed, Venkata Reddy Palleti, and Aditya P. Mathur. 2017. WADI: A Water Distribution Testbed for Research in the Design of Secure Cyber Physical Systems. In Proceedings of the 3rd International Workshop on Cyber-physical Systems for Smart Water Networks. 25--28."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.64.061907"},{"key":"e_1_3_2_1_3_1","volume-title":"Proceedings of the 21th International European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 437--442","author":"Anguita Davide","year":"2013","unstructured":"Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra Perez, and Jorge Luis Reyes Ortiz. 2013. A Public Domain Dataset for Human Activity Recognition Using Smartphones. In Proceedings of the 21th International European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 437--442."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403392"},{"key":"e_1_3_2_1_5_1","volume-title":"Proceedings of the 37th International Conference on Machine Learning. 1597--1607","author":"Chen Ting","unstructured":"Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton. 2020. A Simple Framework for Contrastive Learning of Visual Representations. In Proceedings of the 37th International Conference on Machine Learning. 1597--1607."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.145"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110789"},{"key":"e_1_3_2_1_8_1","first-page":"1","article-title":"Timemae: Self-supervised Representations of Time Series with Decoupled Masked Autoencoders","volume":"14","author":"Cheng Mingyue","year":"2023","unstructured":"Mingyue Cheng, Qi Liu, Zhiding Liu, Hao Zhang, Rujiao Zhang, and Enhong Chen. 2023. Timemae: Self-supervised Representations of Time Series with Decoupled Masked Autoencoders. IEEE Transactions on Knowledge and Data Engineering, Vol. 14, 8 (2023), 1--15.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_1_9_1","first-page":"30750","article-title":"Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning","volume":"36","author":"Demirel Berken Utku","year":"2024","unstructured":"Berken Utku Demirel and Christian Holz. 2024. Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning. Advances in Neural Information Processing Systems, Vol. 36 (2024), 30750--30783.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_10_1","unstructured":"Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai Thomas Unterthiner Mostafa Dehghani Matthias Minderer Georg Heigold Sylvain Gelly et al. 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/324"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119207"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467137"},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 12nd International Conference on Learning Representations. 1--21","author":"Fraikin Archibald","year":"2024","unstructured":"Archibald Fraikin, Adrien Bennetot, and St\u00e9phanie Allassonni\u00e8re. 2024. T-Rep: Representation Learning for Time Series Using Time-embeddings. In Proceedings of the 12nd International Conference on Learning Representations. 1--21."},{"key":"e_1_3_2_1_15_1","first-page":"27356","article-title":"Robust Contrastive Learning Using Negative Samples with Diminished Semantics","volume":"34","author":"Ge Songwei","year":"2021","unstructured":"Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, and David Jacobs. 2021. Robust Contrastive Learning Using Negative Samples with Diminished Semantics. Advances in Neural Information Processing Systems, Vol. 34 (2021), 27356--27368.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_16_1","volume-title":"Proceedings of the 11th International Conference on Critical Information Infrastructures Security. 88--99","author":"Goh Jonathan","year":"2016","unstructured":"Jonathan Goh, Sridhar Adepu, Khurum Nazir Junejo, and Aditya Mathur. 2016. A Dataset to Support Research in the Design of Secure Water Treatment Systems. In Proceedings of the 11th International Conference on Critical Information Infrastructures Security. 88--99."},{"key":"e_1_3_2_1_17_1","volume-title":"An Empirical Survey of Data Augmentation for Time Series Classification with Neural Networks. CoRR","author":"Iwana Brian Kenji","year":"2020","unstructured":"Brian Kenji Iwana and Seiichi Uchida. 2020. An Empirical Survey of Data Augmentation for Time Series Classification with Neural Networks. CoRR, Vol. abs\/2007.15951 (2020)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.111507"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i12.29299"},{"key":"e_1_3_2_1_20_1","first-page":"857","article-title":"Self-supervised Learning: Generative or Contrastive","volume":"35","author":"Liu Xiao","year":"2021","unstructured":"Xiao Liu, Fanjin Zhang, Zhenyu Hou, Li Mian, Zhaoyu Wang, Jing Zhang, and Jie Tang. 2021. Self-supervised Learning: Generative or Contrastive. IEEE Transactions on Knowledge and Data Engineering, Vol. 35, 1 (2021), 857--876.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_1_21_1","first-page":"5879","article-title":"Graph Self-supervised Learning: A Survey","volume":"35","author":"Liu Yixin","year":"2022","unstructured":"Yixin Liu, Ming Jin, Shirui Pan, Chuan Zhou, Yu Zheng, Feng Xia, and S Yu Philip. 2022. Graph Self-supervised Learning: A Survey. IEEE Transactions on Knowledge and Data Engineering, Vol. 35, 6 (2022), 5879--5900.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3675397"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106345"},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of Machine Learning Research. 238--253","author":"Mohsenvand Mostafa Neo","year":"2020","unstructured":"Mostafa Neo Mohsenvand, Mohammad Rasool Izadi, and Pattie Maes. 2020. Contrastive Representation Learning for Electroencephalogram Classification. In Proceedings of Machine Learning Research. 238--253."},{"key":"e_1_3_2_1_25_1","volume-title":"Representation Learning with Contrastive Predictive Coding. arXiv preprint arXiv:1807.03748","author":"van den Oord Aaron","year":"2018","unstructured":"Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation Learning with Contrastive Predictive Coding. arXiv preprint arXiv:1807.03748 (2018)."},{"key":"e_1_3_2_1_26_1","volume-title":"Beril Boga, Esla Timothy Anzaku, Homin Park, Arnout Van Messem, Wesley De Neve, and Joris Vankerschaver.","author":"\u00d6zbulak Utku","year":"2023","unstructured":"Utku \u00d6zbulak, Hyun Jung Lee, Beril Boga, Esla Timothy Anzaku, Homin Park, Arnout Van Messem, Wesley De Neve, and Joris Vankerschaver. 2023. Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training. Transactions on Machine Learning Research (2023), 1--45."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.06.014"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2020.3014842"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3136755.3136817"},{"key":"e_1_3_2_1_31_1","first-page":"5998","article-title":"Attention is All You Need","volume":"30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is All You Need. Advances in Neural Information Processing Systems, Vol. 30 (2017), 5998--6008.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_32_1","volume-title":"Proceedings of the 24th International Joint Conference on Artificial Intelligence. 3939--3945","author":"Wang Zhiguang","year":"2015","unstructured":"Zhiguang Wang and Tim Oates. 2015. Imaging Time-Series to Improve Classification and Imputation. In Proceedings of the 24th International Joint Conference on Artificial Intelligence. 3939--3945."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/631"},{"key":"e_1_3_2_1_34_1","volume-title":"But Useful. In Proceedings of the 16th European Conference on Computer Vision. 126--142","author":"Xuan Hong","year":"2020","unstructured":"Hong Xuan, Abby Stylianou, Xiaotong Liu, and Robert Pless. 2020. Hard Negative Examples are Hard, But Useful. In Proceedings of the 16th European Conference on Computer Vision. 126--142."},{"key":"e_1_3_2_1_35_1","volume-title":"Proceedings of the International Conference on Machine Learning. 25038--25054","author":"Yang Ling","year":"2022","unstructured":"Ling Yang and Shenda Hong. 2022. Unsupervised Time-Series Representation Learning with Iterative Bilinear Temporal-Spectral Fusion. In Proceedings of the International Conference on Machine Learning. 25038--25054."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108606"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.123010"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20881"},{"key":"e_1_3_2_1_39_1","unstructured":"Kexin Zhang Qingsong Wen Chaoli Zhang Rongyao Cai Ming Jin Yong Liu James Y Zhang Yuxuan Liang Guansong Pang Dongjin Song et al. 2024. Self-supervised Learning for Time Series Analysis: Taxonomy Progress and Prospects. IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) 1--20."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.naacl-tutorials.6"},{"key":"e_1_3_2_1_41_1","first-page":"3988","article-title":"Self-Supervised Contrastive Pre-Training For Time Series via Time-frequency Consistency","volume":"35","author":"Zhang Xiang","year":"2022","unstructured":"Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, and Marinka Zitnik. 2022. Self-Supervised Contrastive Pre-Training For Time Series via Time-frequency Consistency. Advances in Neural Information Processing Systems, Vol. 35 (2022), 3988--4003.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.2972125"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2024.3419447"}],"event":{"name":"CIKM '24: The 33rd ACM International Conference on Information and Knowledge Management","location":"Boise ID USA","acronym":"CIKM '24","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 33rd ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627673.3679699","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3627673.3679699","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:58:13Z","timestamp":1750294693000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627673.3679699"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,21]]},"references-count":43,"alternative-id":["10.1145\/3627673.3679699","10.1145\/3627673"],"URL":"https:\/\/doi.org\/10.1145\/3627673.3679699","relation":{},"subject":[],"published":{"date-parts":[[2024,10,21]]},"assertion":[{"value":"2024-10-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}