{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T10:03:41Z","timestamp":1742983421471,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030821920"},{"type":"electronic","value":"9783030821937"}],"license":[{"start":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T00:00:00Z","timestamp":1628035200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T00:00:00Z","timestamp":1628035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-82193-7_16","type":"book-chapter","created":{"date-parts":[[2021,8,3]],"date-time":"2021-08-03T15:23:39Z","timestamp":1628004219000},"page":"248-260","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on Text Classification Modeling Strategy Based on Pre-trained Language Model"],"prefix":"10.1007","author":[{"given":"Yiou","family":"Lin","sequence":"first","affiliation":[]},{"given":"Hang","family":"Lei","sequence":"additional","affiliation":[]},{"given":"Xiaoyu","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Deng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,8,4]]},"reference":[{"issue":"4","key":"16_CR1","first-page":"467","volume":"18","author":"PF Brown","year":"1992","unstructured":"Brown, P.F., Della Pietra, V.J., Desouza, P.V., Lai, J.C., Mercer, R.L.: Class-based n-gram models of natural language. Comput. Linguist. 18(4), 467\u2013480 (1992)","journal-title":"Comput. Linguist."},{"key":"16_CR2","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in Neural Information Processing Systems, vol. 26, pp. 3111\u20133119 (2013)"},{"key":"16_CR3","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"issue":"6","key":"16_CR4","doi-asserted-by":"publisher","first-page":"2505","DOI":"10.1109\/TKDE.2019.2959991","volume":"33","author":"H Peng","year":"2019","unstructured":"Peng, H., et al.: Hierarchical taxonomy-aware and attentional graph capsule RCNNs for large-scale multi-label text classification. IEEE Trans. Knowl. Data Eng. 33(6), 2505\u20132519 (2019)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"16_CR5","doi-asserted-by":"crossref","unstructured":"Safaya, A., Abdullatif, M., Yuret, D.: KUISAIL at SemEval-2020 Task 12: BERT-CNN for offensive speech identification in social media. In: Proceedings of the Fourteenth Workshop on Semantic Evaluation, pp. 2054\u20132059 (2020)","DOI":"10.18653\/v1\/2020.semeval-1.271"},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Wang, Z., et al.: A novel method for intelligent fault diagnosis of bearing based on capsule neural network. Complexity (2019)","DOI":"10.1155\/2019\/6943234"},{"key":"16_CR7","unstructured":"Liu, Y.: Fine-tune BERT for extractive summarization. arXiv preprint arXiv:1903.10318 (2019)"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"Rodrigues Makiuchi, M., Warnita, T., Uto, K., Shinoda, K.: Multimodal fusion of BERT-CNN and gated CNN representations for depression detection. In: Proceedings of the 9th International on Audio\/Visual Emotion Challenge and Workshop, pp. 55\u201363, October 2019","DOI":"10.1145\/3347320.3357694"},{"key":"16_CR9","unstructured":"Peters, M.E., et al.: Deep contextualized word representations. arXiv preprint arXiv:1802.05365 (2018)"},{"key":"16_CR10","unstructured":"Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Improving language understanding by generative pre-training (2018). https:\/\/s3-us-west-2.amazonaws.com\/openaiassets\/researchcovers\/languageunsupervised\/language_understanding_paper.pdf"},{"key":"16_CR11","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"16_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1007\/978-3-642-21735-7_6","volume-title":"Artificial Neural Networks and Machine Learning \u2013 ICANN 2011","author":"GE Hinton","year":"2011","unstructured":"Hinton, G.E., Krizhevsky, A., Wang, S.D.: Transforming auto-encoders. In: Honkela, T., Duch, W., Girolami, M., Kaski, S. (eds.) ICANN 2011. LNCS, vol. 6791, pp. 44\u201351. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-21735-7_6"},{"key":"16_CR13","unstructured":"Sabour, S., Frosst, N., Hinton, G.E.: Dynamic routing between capsules. In: Advances in Neural Information Processing Systems, pp. 3856\u20133866 (2017)"},{"key":"16_CR14","unstructured":"Zhao, W., Ye, J., Yang, M., Lei, Z., Zhang, S., Zhao, Z.: Investigating capsule networks with dynamic routing for text classification. arXiv preprint arXiv:1804.00538 (2018)"},{"key":"16_CR15","unstructured":"Frosst, N., Hinton, G.: Distilling a neural network into a soft decision tree. arXiv preprint arXiv:1711.09784 (2017)"},{"key":"16_CR16","unstructured":"Hinton, G., Vinyals, O., Dean, J.: Distilling the knowledge in a neural network. arXiv preprint arXiv:1503.02531 (2015)"},{"key":"16_CR17","unstructured":"Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., Soricut, R.: ALBERT: a lite BERT for self-supervised learning of language representations. arXiv preprint arXiv:1909.11942 (2019)"},{"key":"16_CR18","unstructured":"Lin, Y., Lei, H., Wu, J., Li, X.: An empirical study on sentiment classification of Chinese review using word embedding. arXiv preprint arXiv:1511.01665 (2015)"},{"key":"16_CR19","unstructured":"Jia, X., Li, N., Jin, Y.: Dynamic convolutional neural network extreme learning machine for text sentiment classification. J. Beijing Univ. Technol. (01), 28\u201335 (2017)"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-82193-7_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,6]],"date-time":"2023-01-06T10:03:06Z","timestamp":1672999386000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-82193-7_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,4]]},"ISBN":["9783030821920","9783030821937"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-82193-7_16","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2021,8,4]]},"assertion":[{"value":"4 August 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IntelliSys","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Proceedings of SAI Intelligent Systems Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"intellisys2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/saiconference.com\/IntelliSys","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}