{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T16:04:40Z","timestamp":1772208280349,"version":"3.50.1"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T00:00:00Z","timestamp":1681344000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T00:00:00Z","timestamp":1681344000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["World Wide Web"],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1007\/s11280-023-01143-5","type":"journal-article","created":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T03:14:54Z","timestamp":1681355694000},"page":"2521-2544","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Few-shot named entity recognition with hybrid multi-prototype learning"],"prefix":"10.1007","volume":"26","author":[{"given":"Zenghua","family":"Liao","sequence":"first","affiliation":[]},{"given":"Junbo","family":"Fei","sequence":"additional","affiliation":[]},{"given":"Weixin","family":"Zeng","sequence":"additional","affiliation":[]},{"given":"Xiang","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,13]]},"reference":[{"key":"1143_CR1","doi-asserted-by":"crossref","unstructured":"Bai, L., Zhang, M., Zhang, H., Zhang, H.: Ftmf: few-shot temporal knowledge graph completion based on meta-optimization and fault-tolerant mechanism. World Wide Web:1\u201328 (2022)","DOI":"10.1007\/s11280-022-01091-6"},{"key":"1143_CR2","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1162\/tacl_a_00104","volume":"4","author":"JPC Chiu","year":"2016","unstructured":"Chiu, J.P.C., Nichols, E.: Named entity recognition with bidirectional lstm-cnns. Trans. Assoc. Comput. Linguis. 4, 357\u2013370 (2016)","journal-title":"Trans. Assoc. Comput. Linguis."},{"key":"1143_CR3","doi-asserted-by":"crossref","unstructured":"Cui, L., Wu, Y., Liu, J., Yang, S., Zhang, Y.: Template-based named entity recognition using BART. In: Findings of the Association for Computational Linguistics: ACL\/IJCNLP 2021, Online Event, August 1-6, 2021, Findings of ACL, vol, ACL\/IJCNLP 2021, pp. 1835\u20131845 (2021)","DOI":"10.18653\/v1\/2021.findings-acl.161"},{"key":"1143_CR4","doi-asserted-by":"publisher","unstructured":"Das, S.S.S., Katiyar, A., Passonneau, R., Zhang, R.: CONTaiNER: few-shot named entity recognition via contrastive learning. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 6338\u20136353. Association for Computational Linguistics, Dublin (2022). https:\/\/doi.org\/10.18653\/v1\/2022.acl-long.439","DOI":"10.18653\/v1\/2022.acl-long.439"},{"key":"1143_CR5","doi-asserted-by":"crossref","unstructured":"Deng, J., Guo, J., Liu, T., Gong, M., Zafeiriou, S.: Sub-center arcface: boosting face recognition by large-scale noisy Web faces. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (eds.) Computer Vision \u2013 ECCV 2020, pp. 741\u2013757. Springer International Publishing, Cham (2020)","DOI":"10.1007\/978-3-030-58621-8_43"},{"key":"1143_CR6","doi-asserted-by":"crossref","unstructured":"Derczynski, L., Nichols, E., van Erp, M., Limsopatham, N.: Results of the WNUT2017 shared task on novel and emerging entity recognition. In: Proceedings of the 3Rd Workshop on Noisy User-generated Text, pp. 140\u2013147. Copenhagen (2017)","DOI":"10.18653\/v1\/W17-4418"},{"key":"1143_CR7","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171\u20134186. Minneapolis (2019)"},{"key":"1143_CR8","doi-asserted-by":"crossref","unstructured":"Ding, N., Xu, G., Chen, Y., Wang, X., Han, X., Xie, P., Zheng, H., Liu, Z.: Few-NERD: a few-shot named entity recognition dataset. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 3198\u20133213. Online (2021)","DOI":"10.18653\/v1\/2021.acl-long.248"},{"key":"1143_CR9","doi-asserted-by":"crossref","unstructured":"Eberts, M., Pech, K., Ulges, A.: Manyent: a dataset for few-shot entity typing. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 5553\u20135557 (2020)","DOI":"10.18653\/v1\/2020.coling-main.486"},{"key":"1143_CR10","doi-asserted-by":"crossref","unstructured":"Feng, X., Feng, X., Qin, B., Feng, Z., Liu, T.: Improving low resource named entity recognition using cross-lingual knowledge transfer. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018, July 13-19, 2018, pp. 4071\u20134077. Stockholm (2018)","DOI":"10.24963\/ijcai.2018\/566"},{"key":"1143_CR11","unstructured":"Finn, C., Abbeel, P., Levine, S.: Model-agnostic meta-learning for fast adaptation of deep networks. In: Precup, D., Teh, Y.W. (eds.) Proceedings of the 34th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol. 70, pp. 1126\u20131135. PMLR (2017). https:\/\/proceedings.mlr.press\/v70\/finn17a.html"},{"key":"1143_CR12","doi-asserted-by":"crossref","unstructured":"Fritzler, A., Logacheva, V., Kretov, M.: Few-shot classification in named entity recognition task. In: Proceedings of the 34th ACM\/SIGAPP Symposium on Applied Computing, SAC \u201919, pp. 993\u20131000. New York (2019)","DOI":"10.1145\/3297280.3297378"},{"key":"1143_CR13","doi-asserted-by":"crossref","unstructured":"Gao, T., Han, X., Zhu, H., Liu, Z., Li, P., Sun, M., Zhou, J.: FewRel 2.0: towards more challenging few-shot relation classification. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint (EMNLP-IJCNLP), pp. 6250\u20136255. Hong Kong (2019)","DOI":"10.18653\/v1\/D19-1649"},{"key":"1143_CR14","doi-asserted-by":"crossref","unstructured":"Han, X., Zhu, H., Yu, P., Wang, Z., Yao, Y., Liu, Z., Sun, M.: FewRel: a large-scale supervised few-shot relation classification dataset with state-of-the-art evaluation. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 4803\u20134809. Brussels (2018)","DOI":"10.18653\/v1\/D18-1514"},{"key":"1143_CR15","doi-asserted-by":"crossref","unstructured":"Hou, Y., Che, W., Lai, Y., Zhou, Z., Liu, Y., Liu, H., Liu, T.: Few-shot slot tagging with collapsed dependency transfer and label-enhanced task-adaptive projection network. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 1381\u20131393. Online (2020)","DOI":"10.18653\/v1\/2020.acl-main.128"},{"key":"1143_CR16","doi-asserted-by":"crossref","unstructured":"Huang, J., Li, C., Subudhi, K., Jose, D., Balakrishnan, S., Chen, W., Peng, B., Gao, J., Han, J.: Few-shot named entity recognition: an empirical baseline study. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 10408\u201310423 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.813"},{"key":"1143_CR17","doi-asserted-by":"crossref","unstructured":"Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., Dyer, C.: Neural architectures for named entity recognition. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 260\u2013270. San Diego (2016)","DOI":"10.18653\/v1\/N16-1030"},{"key":"1143_CR18","unstructured":"Li, J., Chiu, B., Feng, S., Wang, H.: Few-shot named entity recognition via meta-learning. IEEE Trans. Knowl. Data Eng.:1\u20131 (2020)"},{"key":"1143_CR19","doi-asserted-by":"crossref","unstructured":"Li, J., Shang, S., Shao, L.: Metaner: named entity recognition with meta-learning. In: Proceedings of The Web Conference 2020, pp. 429\u2013440 (2020)","DOI":"10.1145\/3366423.3380127"},{"issue":"1","key":"1143_CR20","doi-asserted-by":"publisher","first-page":"453","DOI":"10.1007\/s11280-019-00736-3","volume":"23","author":"M Li","year":"2020","unstructured":"Li, M., Li, Z., Yang, Q., Chen, Z., Zhao, P., Zhao, L.: A crowd-efficient learning approach for ner based on online encyclopedia. World Wide Web 23(1), 453\u2013470 (2020)","journal-title":"World Wide Web"},{"issue":"2","key":"1143_CR21","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1007\/s11280-019-00723-8","volume":"23","author":"X Li","year":"2020","unstructured":"Li, X., Yin, H., Zhou, K., Zhou, X.: Semi-supervised clustering with deep metric learning and graph embedding. World Wide Web 23(2), 781\u2013798 (2020)","journal-title":"World Wide Web"},{"issue":"3","key":"1143_CR22","doi-asserted-by":"publisher","first-page":"1769","DOI":"10.1007\/s11280-019-00758-x","volume":"23","author":"S Lin","year":"2020","unstructured":"Lin, S., Gao, J., Zhang, S., He, X., Sheng, Y., Chen, J.: A continuous learning method for recognizing named entities by integrating domain contextual relevance measurement and web farming mode of web intelligence. World Wide Web 23(3), 1769\u20131790 (2020)","journal-title":"World Wide Web"},{"issue":"2","key":"1143_CR23","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1007\/s11280-018-0601-2","volume":"22","author":"F Liu","year":"2019","unstructured":"Liu, F., Mao, Q., Wang, L., Ruwa, N., Gou, J., Zhan, Y.: An emotion-based responding model for natural language conversation. World Wide Web 22(2), 843\u2013861 (2019)","journal-title":"World Wide Web"},{"issue":"2","key":"1143_CR24","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1007\/s11280-018-0642-6","volume":"22","author":"K Liu","year":"2019","unstructured":"Liu, K., Liu, W., Ma, H., Huang, W., Dong, X.: Generalized zero-shot learning for action recognition with web-scale video data. World Wide Web 22(2), 807\u2013824 (2019)","journal-title":"World Wide Web"},{"key":"1143_CR25","doi-asserted-by":"publisher","unstructured":"Ma, T., Jiang, H., Wu, Q., Zhao, T., Lin, C.Y.: Decomposed meta-learning for few-shot named entity recognition. In: Findings of the Association for Computational Linguistics: ACL 2022, pp. 1584\u20131596. Association for Computational Linguistics, Dublin (2022). https:\/\/doi.org\/10.18653\/v1\/2022.findings-acl.124","DOI":"10.18653\/v1\/2022.findings-acl.124"},{"key":"1143_CR26","unstructured":"Ma, Y., Cambria, E., Gao, S.: Label embedding for zero-shot fine-grained named entity typing. In: COLING 2016, 26th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, December 11-16, 2016, pp. 171\u2013180, Osaka (2016)"},{"key":"1143_CR27","doi-asserted-by":"crossref","unstructured":"Miller, E., Matsakis, N., Viola, P.: Learning from one example through shared densities on transforms. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662), vol. 1, pp. 464\u2013471 (2000)","DOI":"10.1109\/CVPR.2000.855856"},{"key":"1143_CR28","doi-asserted-by":"crossref","unstructured":"Nguyen, H.V., Gelli, F., Poria, S.: DOZEN: cross-domain zero shot named entity recognition with knowledge graph. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1642\u20131646 (2021)","DOI":"10.1145\/3404835.3463113"},{"key":"1143_CR29","doi-asserted-by":"crossref","unstructured":"Petroni, F., Rockt\u00e4schel, T., Riedel, S., Lewis, P.S.H., Bakhtin, A., Wu, Y., Miller, A.H.: Language models as knowledge bases?. 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) pp. 2463\u20132473 (2019)","DOI":"10.18653\/v1\/D19-1250"},{"key":"1143_CR30","unstructured":"Sun, C., Huang, L., Qiu, X.: Utilizing BERT for aspect-based sentiment analysis via constructing auxiliary sentence. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 380\u2013385 (2019)"},{"key":"1143_CR31","doi-asserted-by":"crossref","unstructured":"Sun, S., Sun, Q., Zhou, K., Lv, T.: Hierarchical attention prototypical networks for few-shot 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, November 3-7, 2019, pp. 476\u2013485. Hong Kong (2019)","DOI":"10.18653\/v1\/D19-1045"},{"key":"1143_CR32","doi-asserted-by":"crossref","unstructured":"Tjong Kim Sang, E.F., De Meulder, F.: Introduction to the coNLL-2003 shared task: language-independent named entity recognition. In: Proceedings of the 7th Conference on Natural Language Learning at HLT-NAACL, 2003, pp. 142\u2013147 (2003)","DOI":"10.3115\/1119176.1119195"},{"key":"1143_CR33","doi-asserted-by":"crossref","unstructured":"Tong, M., Wang, S., Xu, B., Cao, Y., Liu, M., Hou, L., Li, J.: Learning from miscellaneous other-class words for few-shot named entity recognition. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 6236\u20136247. Online (2021)","DOI":"10.18653\/v1\/2021.acl-long.487"},{"key":"1143_CR34","doi-asserted-by":"crossref","unstructured":"Tong, M., Wang, S., Xu, B., Cao, Y., Liu, M., Hou, L., Li, J.: Learning from miscellaneous other-class words for few-shot named entity recognition. 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, (Volume 1: Long Papers), Virtual Event, August 1-6, 2021, pp. 6236\u20136247 (2021)","DOI":"10.18653\/v1\/2021.acl-long.487"},{"key":"1143_CR35","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, NIPS\u201917, pp. 6000\u20136010. Curran Associates Inc., Red Hook (2017)"},{"key":"1143_CR36","doi-asserted-by":"publisher","unstructured":"Wang, Y., Chu, H., Zhang, C., Gao, J.: Learning from language description: low-shot named entity recognition via decomposed framework. In: Findings of the Association for Computational Linguistics: EMNLP 2021, pp. 1618\u20131630. Association for Computational Linguistics, Punta Cana (2021). https:\/\/doi.org\/10.18653\/v1\/2021.findings-emnlp.139","DOI":"10.18653\/v1\/2021.findings-emnlp.139"},{"issue":"4","key":"1143_CR37","doi-asserted-by":"publisher","first-page":"102596","DOI":"10.1016\/j.ipm.2021.102596","volume":"58","author":"W Wen","year":"2021","unstructured":"Wen, W., Liu, Y., Ouyang, C., Lin, Q., Chung, T.: Enhanced prototypical network for few-shot relation extraction. Inf. Process. Manag. 58(4), 102596 (2021)","journal-title":"Inf. Process. Manag."},{"key":"1143_CR38","doi-asserted-by":"crossref","unstructured":"Xu, L., Zhang, X., Zhao, X., Chen, H., Chen, F., Choi, J.D.: Boosting cross-lingual transfer via self-learning with uncertainty estimation. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 6716\u20136723 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.538"},{"key":"1143_CR39","doi-asserted-by":"crossref","unstructured":"Yang, Y., Katiyar, A.: Simple and effective few-shot named entity recognition with structured nearest neighbor learning. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 6365\u20136375. Online (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.516"},{"key":"1143_CR40","unstructured":"Yoon, S.W., Seo, J., Moon, J.: TapNet: neural network augmented with task-adaptive projection for few-shot learning. In: Proceedings of the 36th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol. 97, pp. 7115\u20137123 (2019)"},{"key":"1143_CR41","doi-asserted-by":"publisher","unstructured":"Zhong, P., Wang, D., Miao, C.: Knowledge-enriched transformer for emotion detection in textual conversations. 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), pp. 165\u2013176. Association for Computational Linguistics, Hong Kong (2019). https:\/\/doi.org\/10.18653\/v1\/D19-1016","DOI":"10.18653\/v1\/D19-1016"},{"key":"1143_CR42","doi-asserted-by":"crossref","unstructured":"Zhou, J.T., Zhang, H., Jin, D., Zhu, H., Fang, M., Goh, R.S.M., Kwok, K.: Dual adversarial neural transfer for low-resource named entity recognition. In: Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28- August 2, 2019, Volume 1: Long Papers, pp. 3461\u20133471 (2019)","DOI":"10.18653\/v1\/P19-1336"}],"container-title":["World Wide Web"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11280-023-01143-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11280-023-01143-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11280-023-01143-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T01:41:54Z","timestamp":1729215714000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11280-023-01143-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,13]]},"references-count":42,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2023,9]]}},"alternative-id":["1143"],"URL":"https:\/\/doi.org\/10.1007\/s11280-023-01143-5","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-2188949\/v1","asserted-by":"object"}]},"ISSN":["1386-145X","1573-1413"],"issn-type":[{"value":"1386-145X","type":"print"},{"value":"1573-1413","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,13]]},"assertion":[{"value":"21 October 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 December 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 January 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 April 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This declaration is not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Ethics approval and consent to participate"}},{"value":"I declare that all authors have no competing interests as defned by Springer, or other interests that might be perceived to infuence the results and discussion reported in this paper.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Competing interests"}}]}}