{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T18:20:37Z","timestamp":1743099637257,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":29,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789811945489"},{"type":"electronic","value":"9789811945496"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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\/978-981-19-4549-6_12","type":"book-chapter","created":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T20:17:11Z","timestamp":1658434631000},"page":"149-161","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Academic Article Classification Algorithm Based on\u00a0Pre-trained Model and\u00a0Keyword Extraction"],"prefix":"10.1007","author":[{"given":"Zekai","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongyang","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zihan","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronghua","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengyang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengzhe","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,22]]},"reference":[{"key":"12_CR1","unstructured":"Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. In: 3rd International Conference on Learning Representations, ICLR 2015 (2015)"},{"key":"12_CR2","doi-asserted-by":"crossref","unstructured":"Blinov, V., Bolotova-Baranova, V., Braslavski, P.: Large dataset and language model fun-tuning for humor recognition. In: Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, pp. 4027\u20134032 (2019)","DOI":"10.18653\/v1\/P19-1394"},{"key":"12_CR3","unstructured":"Cattle, A., Ma, X.: Recognizing humour using word associations and humour anchor extraction. In: Proceedings of the 27th International Conference on Computational Linguistics, pp. 1849\u20131858 (2018)"},{"key":"12_CR4","doi-asserted-by":"crossref","unstructured":"Conneau, A., et al.: Unsupervised cross-lingual representation learning at scale. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, pp. 8440\u20138451 (2020)","DOI":"10.18653\/v1\/2020.acl-main.747"},{"key":"12_CR5","unstructured":"Devlin, J., Chang, M., 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, NAACL-HLT 2019. pp. 4171\u20134186 (2019)"},{"issue":"1","key":"12_CR6","doi-asserted-by":"publisher","first-page":"50","DOI":"10.15837\/ijccc.2018.1.3142","volume":"13","author":"C Du","year":"2018","unstructured":"Du, C., Huang, L.: Text classification research with attention-based recurrent neural networks. Int. J. Comput. Commun. Control 13(1), 50\u201361 (2018)","journal-title":"Int. J. Comput. Commun. Control"},{"key":"12_CR7","doi-asserted-by":"crossref","unstructured":"Garg, S., Ramakrishnan, G.: Bae: bert-based adversarial examples for text classification (2020). arXiv preprint arXiv:2004.01970","DOI":"10.18653\/v1\/2020.emnlp-main.498"},{"key":"12_CR8","unstructured":"Gui, T., et al.: Textflint: Unified multilingual robustness evaluation toolkit for natural language processing (2021). arXiv preprint arXiv:2103.11441"},{"key":"12_CR9","doi-asserted-by":"crossref","unstructured":"Guy, I., Mejer, A., Nus, A., Raiber, F.: Extracting and ranking travel tips from user-generated reviews. In: Proceedings of the 26th international conference on world wide web, pp. 987\u2013996 (2017)","DOI":"10.1145\/3038912.3052632"},{"key":"12_CR10","doi-asserted-by":"crossref","unstructured":"Johnson, R., Zhang, T.: Deep pyramid convolutional neural networks for text categorization. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, vol. 1(Long Papers), pp. 562\u2013570 (2017)","DOI":"10.18653\/v1\/P17-1052"},{"key":"12_CR11","doi-asserted-by":"crossref","unstructured":"Joulin, A., Grave, E., Bojanowski, P., Mikolov, T.: Bag of tricks for efficient text classification. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017, pp. 427\u2013431 (2017)","DOI":"10.18653\/v1\/E17-2068"},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014, pp. 1746\u20131751 (2014)","DOI":"10.3115\/v1\/D14-1181"},{"key":"12_CR13","doi-asserted-by":"crossref","unstructured":"Lai, S., Xu, L., Liu, K., Zhao, J.: Recurrent convolutional neural networks for text classification. In: Bonet, B., Koenig, S. (eds.) Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, pp. 2267\u20132273 (2015)","DOI":"10.1609\/aaai.v29i1.9513"},{"key":"12_CR14","unstructured":"Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., Soricut, R.: ALBERT: a lite BERT for self-supervised learning of language representations. In: 8th International Conference on Learning Representations, ICLR 2020 (2020)"},{"issue":"12","key":"12_CR15","doi-asserted-by":"publisher","first-page":"2549","DOI":"10.14778\/3407790.3407844","volume":"13","author":"J Li","year":"2020","unstructured":"Li, J., Li, Y., Wang, X., Tan, W.C.: Deep or simple models for semantic tagging? it depends on your data. Proc. VLDB Endowment 13(12), 2549\u20132562 (2020)","journal-title":"Proc. VLDB Endowment"},{"key":"12_CR16","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1007\/978-981-13-3044-5_38","volume-title":"Computer Supported Cooperative Work and Social Computing","author":"R Lin","year":"2019","unstructured":"Lin, R., Fu, C., Mao, C., Wei, J., Li, J.: Academic news text classification model based on attention mechanism and RCNN. In: Sun, Y., Lu, T., Xie, X., Gao, L., Fan, H. (eds.) ChineseCSCW 2018. CCIS, vol. 917, pp. 507\u2013516. Springer, Singapore (2019). https:\/\/doi.org\/10.1007\/978-981-13-3044-5_38"},{"key":"12_CR17","unstructured":"Liu, P., Qiu, X., Huang, X.: Recurrent neural network for text classification with multi-task learning. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, pp. 2873\u20132879 (2016)"},{"key":"12_CR18","unstructured":"Liu, Y., et al.: Roberta: a robustly optimized bert pretraining approach (2019). arXiv preprint arXiv:1907.11692"},{"key":"12_CR19","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. In: 1st International Conference on Learning Representations, ICLR 2013 (2013)"},{"key":"12_CR20","unstructured":"Minaee, S., Kalchbrenner, N., Cambria, E., Nikzad, N., Chenaghlu, M., Gao, J.: Deep learning based text classification: A comprehensive review (2020). arXiv preprint arXiv:2004.03705"},{"key":"12_CR21","doi-asserted-by":"crossref","unstructured":"Negi, S., Daudert, T., Buitelaar, P.: Semeval-2019 task 9: suggestion mining from online reviews and forums. In: Proceedings of the 13th International Workshop on Semantic Evaluation, SemEval@NAACL-HLT 2019, pp. 877\u2013887 (2019)","DOI":"10.18653\/v1\/S19-2151"},{"key":"12_CR22","doi-asserted-by":"crossref","unstructured":"Novgorodov, S., Guy, I., Elad, G., Radinsky, K.: Generating product descriptions from user reviews. In: The World Wide Web Conference, pp. 1354\u20131364 (2019)","DOI":"10.1145\/3308558.3313532"},{"key":"12_CR23","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, pp. 5998\u20136008 (2017)"},{"key":"12_CR24","doi-asserted-by":"crossref","unstructured":"Wan, M., Misra, R., Nakashole, N., McAuley, J.J.: Fine-grained spoiler detection from large-scale review corpora. In: Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, pp. 2605\u20132610 (2019)","DOI":"10.18653\/v1\/P19-1248"},{"key":"12_CR25","doi-asserted-by":"crossref","unstructured":"Yang, D., Lavie, A., Dyer, C., Hovy, E.: Humor recognition and humor anchor extraction. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 2367\u20132376 (2015)","DOI":"10.18653\/v1\/D15-1284"},{"key":"12_CR26","unstructured":"Yang, W., Zhang, H., Lin, J.: Simple applications of bert for ad hoc document retrieval (2019). arXiv preprint arXiv:1903.10972"},{"key":"12_CR27","unstructured":"Yang, Z., Dai, Z., Yang, Y., Carbonell, J.G., Salakhutdinov, R., Le, Q.V.: Xlnet: generalized autoregressive pretraining for language understanding. In: Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, pp. 5754\u20135764 (2019)"},{"key":"12_CR28","doi-asserted-by":"crossref","unstructured":"Yang, Z., Yang, D., Dyer, C., He, X., Smola, A., Hovy, E.: Hierarchical attention networks for document classification. In: Proceedings of the 2016 conference of the North American chapter of the association for computational linguistics: human language technologies, pp. 1480\u20131489 (2016)","DOI":"10.18653\/v1\/N16-1174"},{"key":"12_CR29","doi-asserted-by":"crossref","unstructured":"Yao, L., Mao, C., Luo, Y.: Graph convolutional networks for text classification. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 7370\u20137377 (2019)","DOI":"10.1609\/aaai.v33i01.33017370"}],"container-title":["Communications in Computer and Information Science","Computer Supported Cooperative Work and Social Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-19-4549-6_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T20:19:30Z","timestamp":1658434770000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-19-4549-6_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811945489","9789811945496"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-981-19-4549-6_12","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"22 July 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ChineseCSCW","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF Conference on Computer Supported Cooperative Work  and Social Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Xiangtan","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":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 November 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"chinesecscw2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conf.scholat.com\/home\/ccscw\/2021","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}