{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T22:09:46Z","timestamp":1740175786420,"version":"3.37.3"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:00:00Z","timestamp":1731369600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:00:00Z","timestamp":1731369600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Yunnan Fundamental Research Projects","award":["202401CF070121, 202401BC070021, 202301AS070047"],"award-info":[{"award-number":["202401CF070121, 202401BC070021, 202301AS070047"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62306129, U21B2027, 62366027","62266028"],"award-info":[{"award-number":["62306129, U21B2027, 62366027","62266028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Yunnan Provincial Major Science and Technology Special Plan Projects","award":["202103AA080015, 202202AD080003, 202203AA080004"],"award-info":[{"award-number":["202103AA080015, 202202AD080003, 202203AA080004"]}]},{"name":"Kunming University of Science and Technology \u201cDouble First-rate\u201d Construction Joint Project","award":["202301BE070001-027, 202201BE070001-021"],"award-info":[{"award-number":["202301BE070001-027, 202201BE070001-021"]}]},{"name":"Yunnan High and New Technology Industry Project","award":["201606"],"award-info":[{"award-number":["201606"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s40747-024-01653-3","type":"journal-article","created":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T04:56:42Z","timestamp":1731387402000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Automatical sampling with heterogeneous corpora for grammatical error correction"],"prefix":"10.1007","volume":"11","author":[{"given":"Shichang","family":"Zhu","sequence":"first","affiliation":[]},{"given":"Jianjian","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Ying","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhengtao","family":"Yu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,12]]},"reference":[{"key":"1653_CR1","unstructured":"Afli H, Qiu Z, Way A, Sheridan P (2016) Using SMT for OCR error correction of historical texts. In: Proceedings of LREC"},{"key":"1653_CR2","doi-asserted-by":"publisher","unstructured":"Choe YJ, Ham J, Park K, Yoon Y (2019) A neural grammatical error correction system built on better pre-training and sequential transfer learning. arXiv preprint arXiv:1907.01256. https:\/\/doi.org\/10.18653\/V1\/W19-4423","DOI":"10.18653\/V1\/W19-4423"},{"key":"1653_CR3","doi-asserted-by":"publisher","unstructured":"Duan H, Hsu BP (2011) Online spelling correction for query completion. In: Proceedings of WWW, pp. 117\u2013126. https:\/\/doi.org\/10.1145\/1963405.1963425","DOI":"10.1145\/1963405.1963425"},{"key":"1653_CR4","doi-asserted-by":"publisher","unstructured":"Fang T, Hu J, Wong DF, Wan X, Chao LS, Chang T (2023) Improving grammatical error correction with multimodal feature integration. In: Findings of ACL, pp. 9328\u20139344. https:\/\/doi.org\/10.18653\/V1\/2023.FINDINGS-ACL.594","DOI":"10.18653\/V1\/2023.FINDINGS-ACL.594"},{"key":"1653_CR5","doi-asserted-by":"publisher","unstructured":"Fang T, Liu X, Wong DF, Zhan R, Ding L, Chao LS, Tao D, Zhang M (2023) Transgec: Improving grammatical error correction with translationese. In: Findings of ACL, pp. 3614\u20133633. https:\/\/doi.org\/10.18653\/V1\/2023.FINDINGS-ACL.223","DOI":"10.18653\/V1\/2023.FINDINGS-ACL.223"},{"key":"1653_CR6","unstructured":"Gao J, Li X, Micol D, Quirk C, Sun X (2010) A large scale ranker-based system for search query spelling correction. In: Proceedings of COLING, pp. 358\u2013366"},{"key":"1653_CR7","doi-asserted-by":"publisher","first-page":"395","DOI":"10.21512\/lc.v12i4.4582","volume":"12","author":"MA Ghufron","year":"2018","unstructured":"Ghufron MA (2018) The role of grammarly in assessing english as a foreign language (efl) writing. Lingua Cultura 12:395","journal-title":"Lingua Cultura"},{"key":"1653_CR8","doi-asserted-by":"publisher","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of CVPR, pp. 770\u2013778. https:\/\/doi.org\/10.1109\/CVPR.2016.90","DOI":"10.1109\/CVPR.2016.90"},{"key":"1653_CR9","doi-asserted-by":"publisher","unstructured":"Junczys-Dowmunt M, Grundkiewicz R, Guha S, Heafield K (2018) Approaching neural grammatical error correction as a low-resource machine translation task. In: Proceedings of NAACL, pp. 595\u2013606. https:\/\/doi.org\/10.18653\/V1\/N18-1055","DOI":"10.18653\/V1\/N18-1055"},{"key":"1653_CR10","doi-asserted-by":"publisher","unstructured":"Kubis M, Vetulani Z, Wypych M, Zi\u0119tkiewicz T (2019) Open challenge for correcting errors of speech recognition systems. In: Proceedings of LTC, pp. 322\u2013337. Springer. https:\/\/doi.org\/10.1007\/978-3-031-05328-3_21","DOI":"10.1007\/978-3-031-05328-3_21"},{"key":"1653_CR11","doi-asserted-by":"publisher","unstructured":"Lewis M, Liu Y, Goyal N, Ghazvininejad M, Mohamed A, Levy O, Stoyanov V, Zettlemoyer L (2020) BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In: Proceedings of ACL, pp. 7871\u20137880. https:\/\/doi.org\/10.18653\/V1\/2020.ACL-MAIN.703","DOI":"10.18653\/V1\/2020.ACL-MAIN.703"},{"key":"1653_CR12","doi-asserted-by":"publisher","unstructured":"Li J, Wang Q, Zhu C, Mao Z, Zhang Y (2023) Grammatical error correction via mixed-grained weighted training. In: Findings of EMNLP, pp. 6027\u20136037. https:\/\/doi.org\/10.18653\/V1\/2023.FINDINGS-EMNLP.400","DOI":"10.18653\/V1\/2023.FINDINGS-EMNLP.400"},{"key":"1653_CR13","doi-asserted-by":"publisher","unstructured":"Li Y, Liu X, Wang S, Gong P, Wong DF, Gao Y, Huang H, Zhang M (2023) Templategec: Improving grammatical error correction with detection template. In: Proceedings of ACL, pp. 6878\u20136892. https:\/\/doi.org\/10.18653\/V1\/2023.ACL-LONG.380","DOI":"10.18653\/V1\/2023.ACL-LONG.380"},{"key":"1653_CR14","doi-asserted-by":"publisher","unstructured":"Napoles C, Sakaguchi K, Tetreault JR (2017) JFLEG: A fluency corpus and benchmark for grammatical error correction. In: Proceedings of EACL, pp. 229\u2013234. https:\/\/doi.org\/10.18653\/V1\/E17-2037","DOI":"10.18653\/V1\/E17-2037"},{"key":"1653_CR15","doi-asserted-by":"publisher","unstructured":"Omelianchuk K, Atrasevych V, Chernodub AN, Skurzhanskyi O (2020) Gector - grammatical error correction: Tag, not rewrite. In: Proceedings of ACL, pp. 163\u2013170. https:\/\/doi.org\/10.18653\/V1\/2020.BEA-1.16","DOI":"10.18653\/V1\/2020.BEA-1.16"},{"key":"1653_CR16","doi-asserted-by":"publisher","unstructured":"Stahlberg F, Kumar S (2020) Seq2edits: Sequence transduction using span-level edit operations. In: Proceedings of EMNLP, pp. 5147\u20135159. https:\/\/doi.org\/10.18653\/V1\/2020.EMNLP-MAIN.418","DOI":"10.18653\/V1\/2020.EMNLP-MAIN.418"},{"key":"1653_CR17","doi-asserted-by":"publisher","unstructured":"Tan M, Yang M, Xu R (2023) Focal training and tagger decouple for grammatical error correction. In: Findings of ACL, pp. 5978\u20135985. https:\/\/doi.org\/10.18653\/V1\/2023.FINDINGS-ACL.370","DOI":"10.18653\/V1\/2023.FINDINGS-ACL.370"},{"key":"1653_CR18","doi-asserted-by":"publisher","unstructured":"Vasselli J, Watanabe T (2023) A closer look at k-nearest neighbors grammatical error correction. In: Proceedings of BEA@ACL, pp. 220\u2013231. https:\/\/doi.org\/10.18653\/V1\/2023.BEA-1.19","DOI":"10.18653\/V1\/2023.BEA-1.19"},{"key":"1653_CR19","unstructured":"Wang B, Duan X, Wu D, Che W, Chen Z, Hu G (2022) CCTC: A cross-sentence chinese text correction dataset for native speakers. In: Proceedings of the 29th International Conference on Computational Linguistics, COLING 2022, Gyeongju, Republic of Korea, October 12-17, 2022, pp. 3331\u20133341"},{"key":"1653_CR20","doi-asserted-by":"publisher","unstructured":"Wang H, Dong S, Liu Y, Logan J, Agrawal AK, Liu Y (2020) ASR error correction with augmented transformer for entity retrieval. In: Proceedings of ACL, pp. 1550\u20131554. https:\/\/doi.org\/10.21437\/INTERSPEECH.2020-1753","DOI":"10.21437\/INTERSPEECH.2020-1753"},{"key":"1653_CR21","doi-asserted-by":"publisher","unstructured":"Wang L, Zheng X (2020) Improving grammatical error correction models with purpose-built adversarial examples. In: Proceedings of EMNLP, pp. 2858\u20132869. https:\/\/doi.org\/10.18653\/V1\/2020.EMNLP-MAIN.228","DOI":"10.18653\/V1\/2020.EMNLP-MAIN.228"},{"key":"1653_CR22","unstructured":"Wang W, Bi B, Yan M, Wu C, Xia J, Bao Z, Peng L, Si L (2020) Structbert: Incorporating language structures into pre-training for deep language understanding. In: Proceedings of ICLR"},{"key":"1653_CR23","unstructured":"Wang Y, Kong C, Yang L, Wang Y, Lu X, Hu R, He S, Liu Z, Chen Y, Yang E, Sun M (2021) YACLC: A chinese learner corpus with multidimensional annotation. CoRR abs\/2112.15043"},{"key":"1653_CR24","doi-asserted-by":"publisher","unstructured":"White M, Rozovskaya A (2020) A comparative study of synthetic data generation methods for grammatical error correction. In: Proceedings of BEA@ACL, pp. 198\u2013208. https:\/\/doi.org\/10.18653\/V1\/2020.BEA-1.21","DOI":"10.18653\/V1\/2020.BEA-1.21"},{"key":"1653_CR25","doi-asserted-by":"publisher","unstructured":"Wu X, Wu Y (2022) From spelling to grammar: A new framework for chinese grammatical error correction. In: Findings of EMNLP, pp. 889\u2013902. https:\/\/doi.org\/10.18653\/V1\/2022.FINDINGS-EMNLP.63","DOI":"10.18653\/V1\/2022.FINDINGS-EMNLP.63"},{"key":"1653_CR26","doi-asserted-by":"publisher","unstructured":"Xu L, Wu J, Peng J, Fu J, Cai M (2022) FCGEC: fine-grained corpus for chinese grammatical error correction. In: Findings of EMNLP, pp. 1900\u20131918. https:\/\/doi.org\/10.18653\/V1\/2022.FINDINGS-EMNLP.137","DOI":"10.18653\/V1\/2022.FINDINGS-EMNLP.137"},{"key":"1653_CR27","doi-asserted-by":"publisher","unstructured":"Yakovlev K, Podolskiy A, Bout A, Nikolenko SI, Piontkovskaya I (2023) Gec-depend: Non-autoregressive grammatical error correction with decoupled permutation and decoding. In: Proceedings of ACL, pp. 1546\u20131558. https:\/\/doi.org\/10.18653\/V1\/2023.ACL-LONG.86","DOI":"10.18653\/V1\/2023.ACL-LONG.86"},{"key":"1653_CR28","doi-asserted-by":"publisher","unstructured":"Ye J, Li Y, Li Y, Zheng H (2023) Mixedit: Revisiting data augmentation and beyond for grammatical error correction. In: Findings of EMNLP, pp. 10161\u201310175. https:\/\/doi.org\/10.18653\/V1\/2023.FINDINGS-EMNLP.681","DOI":"10.18653\/V1\/2023.FINDINGS-EMNLP.681"},{"key":"1653_CR29","unstructured":"Yu AW, Dohan D, Luong M, Zhao R, Chen K, Norouzi M, Le QV (2018) Qanet: Combining local convolution with global self-attention for reading comprehension. In: Proceedings of ICLR"},{"key":"1653_CR30","doi-asserted-by":"publisher","unstructured":"Yu L, Lee L, Tseng Y, Chen H (2014) Overview of SIGHAN 2014 bake-off for chinese spelling check. In: Proceedings of CIPS-SIGHAN, pp. 126\u2013132. https:\/\/doi.org\/10.3115\/V1\/W14-6820","DOI":"10.3115\/V1\/W14-6820"},{"key":"1653_CR31","doi-asserted-by":"publisher","unstructured":"Zhang M, Li Z, Fu G, Zhang M (2019) Syntax-enhanced neural machine translation with syntax-aware word representations. In: Proceedings of NAACL. https:\/\/doi.org\/10.18653\/V1\/N19-1118","DOI":"10.18653\/V1\/N19-1118"},{"key":"1653_CR32","doi-asserted-by":"publisher","unstructured":"Zhang Y, Kamigaito H, Okumura M (2023) Bidirectional transformer reranker for grammatical error correction. In: Findings of ACL, pp. 3801\u20133825. https:\/\/doi.org\/10.18653\/V1\/2023.FINDINGS-ACL.234","DOI":"10.18653\/V1\/2023.FINDINGS-ACL.234"},{"key":"1653_CR33","doi-asserted-by":"publisher","unstructured":"Zhang Y, Li Z, Bao Z, Li J, Zhang B, Li C, Huang F, Zhang M (2022) Mucgec: a multi-reference multi-source evaluation dataset for chinese grammatical error correction. In: Proceedings of NAACL-HLT, pp. 3118\u20133130. https:\/\/doi.org\/10.18653\/V1\/2022.NAACL-MAIN.227","DOI":"10.18653\/V1\/2022.NAACL-MAIN.227"},{"key":"1653_CR34","doi-asserted-by":"publisher","unstructured":"Zhang Y, Zhang B, Li Z, Bao Z, Li C, Zhang M (2022) Syngec: Syntax-enhanced grammatical error correction with a tailored gec-oriented parser. In: Proceedings of EMNLP, pp. 2518\u20132531. https:\/\/doi.org\/10.18653\/V1\/2022.EMNLP-MAIN.162","DOI":"10.18653\/V1\/2022.EMNLP-MAIN.162"},{"key":"1653_CR35","doi-asserted-by":"publisher","unstructured":"Zhao W, Wang L, Shen K, Jia R, Liu J (2019) Improving grammatical error correction via pre-training a copy-augmented architecture with unlabeled data. In: Proceedings of NAACL-HLT, pp. 156\u2013165. https:\/\/doi.org\/10.18653\/V1\/N19-1014","DOI":"10.18653\/V1\/N19-1014"},{"key":"1653_CR36","doi-asserted-by":"publisher","unstructured":"Zhao Y, Jiang N, Sun W, Wan X (2018) Overview of the NLPCC 2018 shared task: Grammatical error correction. In: Proceedings pf NLPCC, vol. 11109, pp. 439\u2013445. https:\/\/doi.org\/10.1007\/978-3-319-99501-4_41","DOI":"10.1007\/978-3-319-99501-4_41"},{"key":"1653_CR37","doi-asserted-by":"publisher","unstructured":"Zhao Z, Wang H (2020) Maskgec: Improving neural grammatical error correction via dynamic masking. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 1226\u20131233. https:\/\/doi.org\/10.1609\/AAAI.V34I01.5476","DOI":"10.1609\/AAAI.V34I01.5476"},{"key":"1653_CR38","unstructured":"Ziegler DM, Stiennon N, Wu J, Brown TB, Radford A, Amodei D, Christiano PF, Irving G (2019) Fine-tuning language models from human preferences. CoRR abs\/1909.08593"}],"container-title":["Complex & Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-024-01653-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-024-01653-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-024-01653-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,30]],"date-time":"2025-01-30T20:21:47Z","timestamp":1738268507000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-024-01653-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,12]]},"references-count":38,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["1653"],"URL":"https:\/\/doi.org\/10.1007\/s40747-024-01653-3","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"type":"print","value":"2199-4536"},{"type":"electronic","value":"2198-6053"}],"subject":[],"published":{"date-parts":[[2024,11,12]]},"assertion":[{"value":"2 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 October 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"25"}}