{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T10:36:32Z","timestamp":1756463792582,"version":"3.40.5"},"reference-count":33,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1016\/j.neucom.2024.128719","type":"journal-article","created":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T19:47:28Z","timestamp":1730317648000},"page":"128719","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Breaking the gap between label correlation and instance similarity via new multi-label contrastive learning"],"prefix":"10.1016","volume":"614","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4688-2948","authenticated-orcid":false,"given":"Xin","family":"Wang","sequence":"first","affiliation":[]},{"given":"Wang","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yuhong","family":"Wu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6547-6374","authenticated-orcid":false,"given":"Xingpeng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Chao","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Huayi","family":"Zhan","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.neucom.2024.128719_b1","doi-asserted-by":"crossref","first-page":"1083","DOI":"10.1016\/j.eswa.2014.08.036","article-title":"A multi-label classification based approach for sentiment classification","volume":"42","author":"Liu","year":"2015","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2024.128719_b2","series-title":"International Conference on Big Data and Smart Computing, BigComp 2016","first-page":"215","article-title":"Weighted multi-label classification model for sentiment analysis of online news","author":"Li","year":"2016"},{"key":"10.1016\/j.neucom.2024.128719_b3","series-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"935","article-title":"Extreme multi-label loss functions for recommendation, tagging, ranking & other missing label applications","author":"Jain","year":"2016"},{"key":"10.1016\/j.neucom.2024.128719_b4","series-title":"The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016","first-page":"1480","article-title":"Hierarchical attention networks for document classification","author":"Yang","year":"2016"},{"key":"10.1016\/j.neucom.2024.128719_b5","series-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019","first-page":"4171","article-title":"BERT: pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2019"},{"key":"10.1016\/j.neucom.2024.128719_b6","series-title":"8th International Conference on Learning Representations, ICLR 2020","article-title":"ALBERT: a lite BERT for self-supervised learning of language representations","author":"Lan","year":"2020"},{"key":"10.1016\/j.neucom.2024.128719_b7","series-title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI 2021","first-page":"3363","article-title":"Correlation-guided representation for multi-label text classification","author":"Zhang","year":"2021"},{"key":"10.1016\/j.neucom.2024.128719_b8","series-title":"2017 International Joint Conference on Neural Networks, IJCNN 2017","first-page":"2377","article-title":"Ensemble application of convolutional and recurrent neural networks for multi-label text categorization","author":"Chen","year":"2017"},{"key":"10.1016\/j.neucom.2024.128719_b9","unstructured":"Pengcheng Yang, Xu Sun, Wei Li, Shuming Ma, Wei Wu, Houfeng Wang, SGM: Sequence Generation Model for Multi-label Classification, in: Proceedings of the 27th International Conference on Computational Linguistics, COLING 2018, 2018, pp. 3915\u20133926."},{"key":"10.1016\/j.neucom.2024.128719_b10","doi-asserted-by":"crossref","unstructured":"Wenjie Zhang, Junchi Yan, Xiangfeng Wang, Hongyuan Zha, Deep extreme multi-label learning, in: Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval, 2018, pp. 100\u2013107.","DOI":"10.1145\/3206025.3206030"},{"key":"10.1016\/j.neucom.2024.128719_b11","series-title":"The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2014","first-page":"701","article-title":"DeepWalk: online learning of social representations","author":"Perozzi","year":"2014"},{"key":"10.1016\/j.neucom.2024.128719_b12","series-title":"Advances in Neural Information Processing Systems, NeurIPS 2019","first-page":"5812","article-title":"Attentionxml: Label tree-based attention-aware deep model for high-performance extreme multi-label text classification","author":"You","year":"2019"},{"key":"10.1016\/j.neucom.2024.128719_b13","doi-asserted-by":"crossref","unstructured":"Lin Xiao, Xin Huang, Boli Chen, Liping Jing, Label-specific document representation for multi-label text classification, in: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, 2019, pp. 466\u2013475.","DOI":"10.18653\/v1\/D19-1044"},{"key":"10.1016\/j.neucom.2024.128719_b14","doi-asserted-by":"crossref","unstructured":"Cunxiao Du, Zhaozheng Chen, Fuli Feng, Lei Zhu, Tian Gan, Liqiang Nie, Explicit interaction model towards text classification, in: Proceedings of the AAAI Conference on Artificial Intelligence, AAAI 2020, 2019, pp. 6359\u20136366.","DOI":"10.1609\/aaai.v33i01.33016359"},{"key":"10.1016\/j.neucom.2024.128719_b15","unstructured":"Qianwen Ma, Chunyuan Yuan, Wei Zhou, Songlin Hu, Label-specific dual graph neural network for multi-label text classification, in: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL\/IJCNLP 2021, 2021, pp. 3855\u20133864."},{"key":"10.1016\/j.neucom.2024.128719_b16","series-title":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, ACL 2022","first-page":"672","article-title":"Contrastive learning-enhanced nearest neighbor mechanism for multi-label text classification","author":"Su","year":"2022"},{"year":"2015","series-title":"Convolutional neural network for sentence classification","author":"Chen","key":"10.1016\/j.neucom.2024.128719_b17"},{"key":"10.1016\/j.neucom.2024.128719_b18","doi-asserted-by":"crossref","unstructured":"Jingzhou Liu, Wei-Cheng Chang, Yuexin Wu, Yiming Yang, Deep Learning for Extreme Multi-label Text Classification, in: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017, pp. 115\u2013124.","DOI":"10.1145\/3077136.3080834"},{"key":"10.1016\/j.neucom.2024.128719_b19","doi-asserted-by":"crossref","unstructured":"Qi Qin, Wenpeng Hu, Bing Liu, Feature projection for improved text classification, in: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, 2020, pp. 8161\u20138171.","DOI":"10.18653\/v1\/2020.acl-main.726"},{"key":"10.1016\/j.neucom.2024.128719_b20","doi-asserted-by":"crossref","unstructured":"Qipeng Guo, Xipeng Qiu, Pengfei Liu, Xiangyang Xue, Zheng Zhang, Multi-scale self-attention for text classification, in: Proceedings of the AAAI Conference on Artificial Intelligence, IAAI 2020, 2020, pp. 7847\u20137854.","DOI":"10.1609\/aaai.v34i05.6290"},{"key":"10.1016\/j.neucom.2024.128719_b21","doi-asserted-by":"crossref","unstructured":"Xien Liu, Xinxin You, Xiao Zhang, Ji Wu, Ping Lv, Tensor graph convolutional networks for text classification, in: Proceedings of the AAAI Conference on Artificial Intelligence, IAAI 2020, 2020, pp. 8409\u20138416.","DOI":"10.1609\/aaai.v34i05.6359"},{"issue":"5","key":"10.1016\/j.neucom.2024.128719_b22","doi-asserted-by":"crossref","first-page":"124:1","DOI":"10.1145\/3643853","article-title":"On the value of head labels in multi-label text classification","volume":"18","author":"Wang","year":"2024","journal-title":"ACM Trans. Knowl. Discov. Data"},{"key":"10.1016\/j.neucom.2024.128719_b23","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.111303","article-title":"Multi-label text classification based on semantic-sensitive graph convolutional network","volume":"284","author":"Zeng","year":"2024","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.neucom.2024.128719_b24","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.111878","article-title":"Multi-label text classification model integrating label attention and historical attention","volume":"296","author":"Sun","year":"2024","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.neucom.2024.128719_b25","series-title":"Advances in Neural Information Processing Systems, NeurIPS 2017","first-page":"5413","article-title":"Maximizing subset accuracy with recurrent neural networks in multi-label classification","author":"Nam","year":"2017"},{"issue":"6","key":"10.1016\/j.neucom.2024.128719_b26","doi-asserted-by":"crossref","first-page":"2716","DOI":"10.1109\/TKDE.2023.3323401","article-title":"Variational continuous label distribution learning for multi-label text classification","volume":"36","author":"Zhao","year":"2024","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.neucom.2024.128719_b27","unstructured":"Pengcheng Yang, Fuli Luo, Shuming Ma, Junyang Lin, Xu Sun, A deep reinforced sequence-to-set model for multi-label classification, in: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, ACL 2019, 2019, pp. 5252\u20135258."},{"key":"10.1016\/j.neucom.2024.128719_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.127671","article-title":"Label-text bi-attention capsule networks model for multi-label text classification","volume":"588","author":"Wang","year":"2024","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2024.128719_b29","series-title":"Findings of the Association for Computational Linguistics: ACL 2023, Toronto, Canada, July 9-14, 2023","first-page":"8730","article-title":"An effective deployment of contrastive learning in multi-label text classification","author":"Lin","year":"2023"},{"key":"10.1016\/j.neucom.2024.128719_b30","series-title":"Proceedings of the the 17th International Workshop on Semantic Evaluation, SemEval@ACL 2023, Toronto, Canada, 13-14 July 2023","first-page":"426","article-title":"Mao-zedong at SemEval-2023 task 4: Label represention multi-head attention model with contrastive learning-enhanced nearest neighbor mechanism for multi-label text classification","author":"Zhang","year":"2023"},{"key":"10.1016\/j.neucom.2024.128719_b31","first-page":"361","article-title":"RCV1: a new benchmark collection for text categorization research","volume":"5","author":"Lewis","year":"2004","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.neucom.2024.128719_b32","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v37i9.26259","article-title":"Label-specific feature augmentation for long-tailed multi-label text classification","author":"Xu","year":"2023"},{"key":"10.1016\/j.neucom.2024.128719_b33","article-title":"Roberta: A robustly optimized BERT pretraining approach","author":"Liu","year":"2019","journal-title":"CoRR"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231224014905?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231224014905?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T08:28:16Z","timestamp":1733128096000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231224014905"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":33,"alternative-id":["S0925231224014905"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2024.128719","relation":{},"ISSN":["0925-2312"],"issn-type":[{"type":"print","value":"0925-2312"}],"subject":[],"published":{"date-parts":[[2025,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Breaking the gap between label correlation and instance similarity via new multi-label contrastive learning","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2024.128719","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"128719"}}