{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T19:38:53Z","timestamp":1742931533579,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":18,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819947485"},{"type":"electronic","value":"9789819947492"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-99-4749-2_41","type":"book-chapter","created":{"date-parts":[[2023,7,29]],"date-time":"2023-07-29T23:02:17Z","timestamp":1690671737000},"page":"485-496","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-task Question Generation Based Data Augmentation for Biomedical Answer Generation"],"prefix":"10.1007","author":[{"given":"Junting","family":"Zhao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Bai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenge","family":"Rong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanxin","family":"Ouyang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhang","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,30]]},"reference":[{"key":"41_CR1","doi-asserted-by":"crossref","unstructured":"Alberti, C., Andor, D., Pitler, E., Devlin, J., Collins, M.: Synthetic QA corpora generation with roundtrip consistency. In: Proceedings of the 57th Conference of the Association for Computational Linguistics, pp. 6168\u20136173 (2019)","DOI":"10.18653\/v1\/P19-1620"},{"key":"41_CR2","doi-asserted-by":"crossref","unstructured":"Chen, W., Verga, P., de Jong, M., Wieting, J., Cohen, W.W.: Augmenting pre-trained language models with QA-memory for open-domain question answering. CoRR abs\/2204.04581 (2022)","DOI":"10.18653\/v1\/2023.eacl-main.117"},{"key":"41_CR3","doi-asserted-by":"crossref","unstructured":"Du, X., Shao, J., Cardie, C.: Learning to ask: neural question generation for reading comprehension. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pp. 1342\u20131352 (2017)","DOI":"10.18653\/v1\/P17-1123"},{"key":"41_CR4","doi-asserted-by":"crossref","unstructured":"Feng, S.Y., et al.: A survey of data augmentation approaches for NLP. In: Findings of the Association for Computational Linguistics: ACL\/IJCNLP, pp. 968\u2013988 (2021)","DOI":"10.18653\/v1\/2021.findings-acl.84"},{"key":"41_CR5","unstructured":"Fu, Y., Ou, W., Yu, Z., Lin, Y.: MIGA: a unified multi-task generation framework for conversational text-to-SQL. CoRR abs\/2212.09278 (2022)"},{"key":"41_CR6","doi-asserted-by":"crossref","unstructured":"Gu, Y., et al.: Domain-specific language model pretraining for biomedical natural language processing. ACM Trans. Comput. Healthc. 3(1), 2:1\u20132:23 (2022)","DOI":"10.1145\/3458754"},{"key":"41_CR7","unstructured":"Heilman, M., Smith, N.A.: Good question! Statistical ranking for question generation. In: Proceedings of the 2010 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 609\u2013617 (2010)"},{"key":"41_CR8","doi-asserted-by":"crossref","unstructured":"Jin, Q., et al.: Biomedical question answering: a survey of approaches and challenges. ACM Comput. Surv. 55(2), 35:1\u201335:36 (2023)","DOI":"10.1145\/3490238"},{"key":"41_CR9","unstructured":"Lewis, M., Fan, A.: Generative question answering: learning to answer the whole question. In: Proceedings of the 7th International Conference on Learning Representations (2019)"},{"key":"41_CR10","doi-asserted-by":"crossref","unstructured":"Lewis, M., et al.: BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 7871\u20137880 (2020)","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"41_CR11","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.1162\/tacl_a_00415","volume":"9","author":"PSH Lewis","year":"2021","unstructured":"Lewis, P.S.H., et al.: PAQ: 65 million probably-asked questions and what you can do with them. Trans. Assoc. Comput. Linguist. 9, 1098\u20131115 (2021)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"41_CR12","doi-asserted-by":"crossref","unstructured":"Lyu, C., Shang, L., Graham, Y., Foster, J., Jiang, X., Liu, Q.: Improving unsupervised question answering via summarization-informed question generation. In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pp. 4134\u20134148 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.340"},{"key":"41_CR13","unstructured":"Raffel, C., et al.: Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21, 140:1\u2013140:67 (2020)"},{"key":"41_CR14","doi-asserted-by":"crossref","unstructured":"Rajpurkar, P., Zhang, J., Lopyrev, K., Liang, P.: SQuAD: 100, 000+ questions for machine comprehension of text. In: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pp. 2383\u20132392 (2016)","DOI":"10.18653\/v1\/D16-1264"},{"key":"41_CR15","doi-asserted-by":"crossref","unstructured":"Tsatsaronis, G., et al.: An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition. BMC Bioinform. 16, 138:1\u2013138:28 (2015)","DOI":"10.1186\/s12859-015-0564-6"},{"key":"41_CR16","doi-asserted-by":"crossref","unstructured":"Wei, J.W., Zou, K.: EDA: easy data augmentation techniques for boosting performance on text classification tasks. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, pp. 6381\u20136387 (2019)","DOI":"10.18653\/v1\/D19-1670"},{"key":"41_CR17","doi-asserted-by":"crossref","unstructured":"Yang, W., Xie, Y., Tan, L., Xiong, K., Li, M., Lin, J.: Data augmentation for BERT fine-tuning in open-domain question answering. CoRR abs\/1904.06652 (2019)","DOI":"10.18653\/v1\/N19-4013"},{"key":"41_CR18","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1007\/978-3-030-43887-6_64","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"W Yoon","year":"2020","unstructured":"Yoon, W., Lee, J., Kim, D., Jeong, M., Kang, J.: Pre-trained language model for biomedical question answering. In: Cellier, P., Driessens, K. (eds.) ECML PKDD 2019. CCIS, vol. 1168, pp. 727\u2013740. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-43887-6_64"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-4749-2_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,18]],"date-time":"2023-12-18T02:59:10Z","timestamp":1702868350000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-4749-2_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819947485","9789819947492"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-4749-2_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"30 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zhengzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 August 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2023a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2023\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}