{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T19:06:52Z","timestamp":1743102412632,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031446955"},{"type":"electronic","value":"9783031446962"}],"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\/978-3-031-44696-2_61","type":"book-chapter","created":{"date-parts":[[2023,10,7]],"date-time":"2023-10-07T09:03:59Z","timestamp":1696669439000},"page":"787-798","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Hybrid Summarization Method for Legal Judgment Documents Based on Lawformer"],"prefix":"10.1007","author":[{"given":"Jingpei","family":"Dan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weixuan","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lanlin","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuming","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingfei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,8]]},"reference":[{"key":"61_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2021.100388","volume":"40","author":"D Jain","year":"2021","unstructured":"Jain, D., Borah, M.D., Biswas, A.: Summarization of legal documents: where are we now and the way forward. Comput. Sci. Rev. 40, 100388 (2021)","journal-title":"Comput. Sci. Rev."},{"issue":"5","key":"61_CR2","first-page":"2141","volume":"34","author":"D Anand","year":"2022","unstructured":"Anand, D., Wagh, R.: Effective deep learning approaches for summarization of legal texts. J. King Saud Univ. \u2013 Comput. Inform. Sci. 34(5), 2141\u20132150 (2022)","journal-title":"J. King Saud Univ. \u2013 Comput. Inform. Sci."},{"key":"61_CR3","doi-asserted-by":"crossref","unstructured":"Zhong, H., Xiao, C., et al.: How does NLP benefit legal system: a summary of legal artificial intelligence. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 5218\u20135230 (2020)","DOI":"10.18653\/v1\/2020.acl-main.466"},{"key":"61_CR4","doi-asserted-by":"crossref","unstructured":"Zhong, L., Zhong, Z., et al.: Automatic summarization of legal decisions using iterative masking of predictive sentences. In: Proceedings of the 17th International Conference on Artificial Intelligence and Law, pp. 163\u2013172 (2019)","DOI":"10.1145\/3322640.3326728"},{"key":"61_CR5","doi-asserted-by":"crossref","unstructured":"Nguyen, D., Nguyen, B., et al.: Robust deep reinforcement learning for extractive legal summarization. In: Neural Information Processing, pp. 597\u2013604 (2021)","DOI":"10.1007\/978-3-030-92310-5_69"},{"key":"61_CR6","doi-asserted-by":"crossref","unstructured":"Gao, Y., Liu, Z., et al.: Extractive summarization of Chinese judgment documents via sentence embedding and memory network. In: CCF International Conference on Natural Language Processing and Chinese Computing, pp. 413\u2013424 (2021)","DOI":"10.1007\/978-3-030-88480-2_33"},{"key":"61_CR7","unstructured":"Elaraby, M., Litman, D.: ArgLegalSumm: Improving abstractive summarization of legal documents with argument mining. arXiv:2209.01650 (2022)"},{"key":"61_CR8","doi-asserted-by":"crossref","unstructured":"Yoon, J., Muhammad, J., et al.: Abstractive summarization of Korean legal cases using pre-trained language models. In: 16th International Conference on Ubiquitous Information Management and Communication, pp. 1\u20137 (2022)","DOI":"10.1109\/IMCOM53663.2022.9721808"},{"key":"61_CR9","first-page":"376","volume-title":"KSEM 2021, LNCS","author":"J Liu","year":"2021","unstructured":"Liu, J., Wu, J., Luo, X.: Chinese judicial summarising based on short sentence extraction and GPT-2. In: Qiu, H., Zhang, C., et al. (eds.) KSEM 2021, LNCS, vol. 12816, pp. 376\u2013393. Springer, Cham (2021)"},{"issue":"8","key":"61_CR10","first-page":"9","volume":"1","author":"A Radford","year":"2019","unstructured":"Radford, A., Wu, J., et al.: Language models are unsupervised multitask learners. OpenAI Blog 1(8), 9 (2019)","journal-title":"OpenAI Blog"},{"key":"61_CR11","first-page":"486","volume-title":"CLAR 2021, LNCS","author":"Y Gao","year":"2021","unstructured":"Gao, Y., Liu, Z., et al.: Extractive-abstractive summarization of judgment documents using multiple attention networks. In: Baroni, P., et al. (eds.) CLAR 2021, LNCS, vol. 13040, pp. 486\u2013494. Springer, Cham (2021)"},{"key":"61_CR12","unstructured":"Dong, L., Yang, N., et al.: Unified language model pre-training for natural language understanding and generation. In: 33rd Conference on Neural Information Processing Systems, pp. 13042\u201313054 (2019)"},{"key":"61_CR13","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.aiopen.2021.06.003","volume":"2","author":"C Xiao","year":"2021","unstructured":"Xiao, C., Hu, X., et al.: Lawformer: a pre-trained language model for chinese legal long documents. AI Open 2, 79\u201384 (2021)","journal-title":"AI Open"},{"key":"61_CR14","unstructured":"Liu, Y.: Fine-tune BERT for Extractive Summarization. arXiv:1903.10318 (2019)"},{"key":"61_CR15","unstructured":"Vaswani, A., Shazeer, N., et al.: Attention is all you need. In: Annual Conference on Neural Information Processing Systems, pp. 5998\u20136008 (2017)"},{"key":"61_CR16","doi-asserted-by":"crossref","unstructured":"Nallapati, R., Zhou, B., et al.: Abstractive text summarization using sequence-to-sequence RNNs and beyond. In: Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, pp. 280\u2013290 (2016)","DOI":"10.18653\/v1\/K16-1028"},{"key":"61_CR17","doi-asserted-by":"crossref","unstructured":"See, A., Liu, P.J., Manning, C.D.: Get to the point: summarization with pointer-generator networks. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pp. 1073\u20131083 (2017)","DOI":"10.18653\/v1\/P17-1099"},{"key":"61_CR18","unstructured":"Devlin, J., Chang, M., et al.: 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, pp. 4171\u20134186 (2019)"},{"key":"61_CR19","unstructured":"Lin, C.Y.: ROUGE: A package for automatic evaluation of summaries. In: Text Summarization Branches Out, pp. 74\u201381 (2004)"},{"key":"61_CR20","doi-asserted-by":"crossref","unstructured":"Mihalcea, R., Tarau, P.: TextRank: Bringing order into text. In: Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, pp.404\u2013411 (2004)","DOI":"10.3115\/1220575.1220627"}],"container-title":["Lecture Notes in Computer Science","Natural Language Processing and Chinese Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-44696-2_61","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T09:02:26Z","timestamp":1730278946000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-44696-2_61"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031446955","9783031446962"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-44696-2_61","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":"8 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NLPCC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"CCF International Conference on Natural Language Processing and Chinese Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Foshan","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":"12 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"nlpcc2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/tcci.ccf.org.cn\/conference\/2023\/index.php","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":"Softconf","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"478","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":"143","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":"0","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":"30% - 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":"3","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":"4","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}