{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:15:30Z","timestamp":1742912130526,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030731960"},{"type":"electronic","value":"9783030731977"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-73197-7_1","type":"book-chapter","created":{"date-parts":[[2021,4,6]],"date-time":"2021-04-06T19:03:01Z","timestamp":1617735781000},"page":"3-19","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Multi-label Classification of Long Text Based on Key-Sentences Extraction"],"prefix":"10.1007","author":[{"given":"Jiayin","family":"Chen","sequence":"first","affiliation":[]},{"given":"Xiaolong","family":"Gong","sequence":"additional","affiliation":[]},{"given":"Ye","family":"Qiu","sequence":"additional","affiliation":[]},{"given":"Xi","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Zhiyi","family":"Ma","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,4,6]]},"reference":[{"key":"1_CR1","doi-asserted-by":"crossref","unstructured":"Aly, R., Remus, S., Biemann, C.: Hierarchical multi-label classification of text with capsule networks. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pp. 323\u2013330 (2019)","DOI":"10.18653\/v1\/P19-2045"},{"key":"1_CR2","doi-asserted-by":"crossref","unstructured":"Banerjee, S., Akkaya, C., Perez-Sorrosal, F., Tsioutsiouliklis, K.: Hierarchical transfer learning for multi-label text classification. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 6295\u20136300 (2019)","DOI":"10.18653\/v1\/P19-1633"},{"issue":"9","key":"1_CR3","doi-asserted-by":"publisher","first-page":"1757","DOI":"10.1016\/j.patcog.2004.03.009","volume":"37","author":"MR Boutell","year":"2004","unstructured":"Boutell, M.R., Luo, J., Shen, X., Brown, C.M.: Learning multi-label scene classification. Pattern Recogn. 37(9), 1757\u20131771 (2004)","journal-title":"Pattern Recogn."},{"key":"1_CR4","unstructured":"Brandt, J.: Imbalanced multi-label classification using multi-task learning with extractive summarization. arXiv preprint arXiv:1903.06963 (2019)"},{"key":"1_CR5","doi-asserted-by":"crossref","unstructured":"Chalkidis, I., Fergadiotis, M., Malakasiotis, P., Androutsopoulos, I.: Large-scale multi-label text classification on eu legislation. arXiv preprint arXiv:1906.02192 (2019)","DOI":"10.18653\/v1\/P19-1636"},{"key":"1_CR6","unstructured":"Chiang, T.H., Lo, H.Y., Lin, S.D.: A ranking-based knn approach for multi-label classification. In: Asian Conference on Machine Learning, pp. 81\u201396 (2012)"},{"key":"1_CR7","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)"},{"key":"1_CR8","doi-asserted-by":"crossref","unstructured":"Dong, H., Wang, W., Huang, K., Coenen, F.: Joint multi-label attention networks for social text annotation. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 1 (Long and Short Papers), pp. 1348\u20131354 (2019)","DOI":"10.18653\/v1\/N19-1136"},{"issue":"2","key":"1_CR9","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s10994-008-5064-8","volume":"73","author":"J F\u00fcrnkranz","year":"2008","unstructured":"F\u00fcrnkranz, J., H\u00fcllermeier, E., Menc\u00eda, E.L., Brinker, K.: Multilabel classification via calibrated label ranking. Mach. Learn. 73(2), 133\u2013153 (2008)","journal-title":"Mach. Learn."},{"key":"1_CR10","doi-asserted-by":"crossref","unstructured":"Ghamrawi, N., McCallum, A.: Collective multi-label classification. In: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 195\u2013200 (2005)","DOI":"10.1145\/1099554.1099591"},{"key":"1_CR11","doi-asserted-by":"crossref","unstructured":"He, R., Lee, W.S., Ng, H.T., Dahlmeier, D.: An interactive multi-task learning network for end-to-end aspect-based sentiment analysis. arXiv preprint arXiv:1906.06906 (2019)","DOI":"10.18653\/v1\/P19-1048"},{"issue":"8","key":"1_CR12","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"1_CR13","unstructured":"Hu, Z., Li, X., Tu, C., Liu, Z., Sun, M.: Few-shot charge prediction with discriminative legal attributes. In: Proceedings of the 27th International Conference on Computational Linguistics, pp. 487\u2013498 (2018)"},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Huang, W., et al.: Hierarchical multi-label text classification: an attention-based recurrent network approach. In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 1051\u20131060 (2019)","DOI":"10.1145\/3357384.3357885"},{"key":"1_CR15","doi-asserted-by":"crossref","unstructured":"Kim, Y.: Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882 (2014)","DOI":"10.3115\/v1\/D14-1181"},{"key":"1_CR16","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":"1_CR17","doi-asserted-by":"crossref","unstructured":"Liu, J., Chang, W.C., Wu, Y., Yang, Y.: Deep learning for extreme multi-label text classification. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 115\u2013124 (2017)","DOI":"10.1145\/3077136.3080834"},{"key":"1_CR18","unstructured":"Liu, W.: Copula multi-label learning. In: Advances in Neural Information Processing Systems, pp. 6337\u20136346 (2019)"},{"key":"1_CR19","doi-asserted-by":"crossref","unstructured":"Maddela, M., Xu, W., Preo\u0163iuc-Pietro, D.: Multi-task pairwise neural ranking for hashtag segmentation. arXiv preprint arXiv:1906.00790 (2019)","DOI":"10.18653\/v1\/P19-1242"},{"key":"1_CR20","doi-asserted-by":"crossref","unstructured":"Schindler, A., Knees, P.: Multi-task music representation learning from multi-label embeddings. In: 2019 International Conference on Content-Based Multimedia Indexing (CBMI), pp. 1\u20136. IEEE (2019)","DOI":"10.1109\/CBMI.2019.8877462"},{"key":"1_CR21","doi-asserted-by":"crossref","unstructured":"Shimura, K., Li, J., Fukumoto, F.: HFT-CNN: learning hierarchical category structure for multi-label short text categorization. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 811\u2013816 (2018)","DOI":"10.18653\/v1\/D18-1093"},{"key":"1_CR22","doi-asserted-by":"crossref","unstructured":"Tian, B., Zhang, Y., Wang, J., Xing, C.: Hierarchical inter-attention network for document classification with multi-task learning. In: IJCAI, pp. 3569\u20133575 (2019)","DOI":"10.24963\/ijcai.2019\/495"},{"key":"1_CR23","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"406","DOI":"10.1007\/978-3-540-74958-5_38","volume-title":"Machine Learning: ECML 2007","author":"G Tsoumakas","year":"2007","unstructured":"Tsoumakas, G., Vlahavas, I.: Random k-labelsets: an ensemble method for multilabel classification. In: Kok, J.N., Koronacki, J., Mantaras, R.L., Matwin, S., Mladeni\u010d, D., Skowron, A. (eds.) ECML 2007. LNCS (LNAI), vol. 4701, pp. 406\u2013417. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-74958-5_38"},{"key":"1_CR24","doi-asserted-by":"crossref","unstructured":"Wang, H., Liu, W., Zhao, Y., Zhang, C., Hu, T., Chen, G.: Discriminative and correlative partial multi-label learning. In: IJCAI, pp. 3691\u20133697 (2019)","DOI":"10.24963\/ijcai.2019\/512"},{"key":"1_CR25","doi-asserted-by":"crossref","unstructured":"Xie, M.K., Huang, S.J.: Partial multi-label learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32 (2018)","DOI":"10.1609\/aaai.v32i1.11644"},{"key":"1_CR26","unstructured":"Yang, P., Sun, X., Li, W., Ma, S., Wu, W., Wang, H.: SGM: sequence generation model for multi-label classification. arXiv preprint arXiv:1806.04822 (2018)"},{"key":"1_CR27","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":"1_CR28","doi-asserted-by":"crossref","unstructured":"Ye, W., Li, B., Xie, R., Sheng, Z., Chen, L., Zhang, S.: Exploiting entity bio tag embeddings and multi-task learning for relation extraction with imbalanced data. arXiv preprint arXiv:1906.08931 (2019)","DOI":"10.18653\/v1\/P19-1130"},{"key":"1_CR29","unstructured":"You, R., Zhang, Z., Wang, Z., Dai, S., Mamitsuka, H., Zhu, S.: Attentionxml: label tree-based attention-aware deep model for high-performance extreme multi-label text classification. In: Advances in Neural Information Processing Systems, pp. 5820\u20135830 (2019)"},{"issue":"7","key":"1_CR30","doi-asserted-by":"publisher","first-page":"2038","DOI":"10.1016\/j.patcog.2006.12.019","volume":"40","author":"ML Zhang","year":"2007","unstructured":"Zhang, M.L., Zhou, Z.H.: ML-KNN: a lazy learning approach to multi-label learning. Pattern Recogn. 40(7), 2038\u20132048 (2007)","journal-title":"Pattern Recogn."},{"issue":"8","key":"1_CR31","doi-asserted-by":"publisher","first-page":"1819","DOI":"10.1109\/TKDE.2013.39","volume":"26","author":"ML Zhang","year":"2013","unstructured":"Zhang, M.L., Zhou, Z.H.: A review on multi-label learning algorithms. IEEE Trans. Knowl. Data Eng. 26(8), 1819\u20131837 (2013)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"1_CR32","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Liu, J., Razavian, N.: Bert-xml: Large scale automated ICD coding using bert pretraining. arXiv preprint arXiv:2006.03685 (2020)","DOI":"10.18653\/v1\/2020.clinicalnlp-1.3"},{"issue":"6","key":"1_CR33","doi-asserted-by":"publisher","first-page":"1081","DOI":"10.1109\/TKDE.2017.2785795","volume":"30","author":"Y Zhu","year":"2017","unstructured":"Zhu, Y., Kwok, J.T., Zhou, Z.H.: Multi-label learning with global and local label correlation. IEEE Trans. Knowl. Data Eng. 30(6), 1081\u20131094 (2017)","journal-title":"IEEE Trans. Knowl. Data Eng."}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-73197-7_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T14:56:31Z","timestamp":1671807391000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-73197-7_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030731960","9783030731977"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-73197-7_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"6 April 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DASFAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database Systems for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Taipei","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Taiwan","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":"11 April 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dasfaa2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/dm.iis.sinica.edu.tw\/DASFAA2021\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"490","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"98","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"33","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the Corona pandemic this event was held virtually.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}