{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T04:02:31Z","timestamp":1771992151846,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":44,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T00:00:00Z","timestamp":1734307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,12,16]]},"DOI":"10.1145\/3677389.3702584","type":"proceedings-article","created":{"date-parts":[[2025,3,13]],"date-time":"2025-03-13T16:53:52Z","timestamp":1741884832000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Decoding the Essence of Scientific Knowledge Entity Extraction: An Innovative MRC Framework with Semantic Contrastive Learning and Boundary Perception"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-8451-1452","authenticated-orcid":false,"given":"Yang","family":"Li","sequence":"first","affiliation":[{"name":"National Science Library, Chinese Academy of Sciences, Beijing, China"},{"name":"University of Chinese Academy of Sciences, Beijing, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9941-7548","authenticated-orcid":false,"given":"Mengting","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Science Library, Chinese Academy of Science, Beijing, China"},{"name":"University of Chinese Academy of Sciences, Beijing, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1596-7487","authenticated-orcid":false,"given":"Zhixiong","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Science Library, Chinese Academy of Science, Beijing, China"},{"name":"University of Chinese Academy of Sciences, Beijing, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4009-9523","authenticated-orcid":false,"given":"Yajiao","family":"Wang","sequence":"additional","affiliation":[{"name":"National Science Library, Chinese Academy of Science, Beijing, China"},{"name":"University of Chinese Academy of Sciences, Beijing, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,3,13]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"SciBERT: A pretrained language model for scientific text. arXiv preprint arXiv:1903.10676","author":"Beltagy Iz","year":"2019","unstructured":"Iz Beltagy, Kyle Lo, and Arman Cohan. 2019. SciBERT: A pretrained language model for scientific text. arXiv preprint arXiv:1903.10676 (2019)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","unstructured":"Yuxiang Cai Da Luo Yanglei Gan Rui Hou Xueyi Liu Qiao Liu and Xiaojun Shi. [n. d.]. Nested Named Entity Recognition Based on Span Boundary Perception. Journal of Software ([n.d.]) 1--14. [In Chinese]. 10.13328\/j.cnki.jos.007040","DOI":"10.13328\/j.cnki.jos.007040"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-022-02059-2"},{"key":"e_1_3_2_1_4_1","unstructured":"Nancy Chinchor and Elaine Marsh. 1998. Muc-7 information extraction task definition. In Proceeding of the seventh message understanding conference (MUC-7) Appendices. 359--367."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0071416"},{"key":"e_1_3_2_1_6_1","volume-title":"Framewise phoneme classification with bidirectional LSTM and other neural network architectures. Neural networks 18, 5--6","author":"Graves Alex","year":"2005","unstructured":"Alex Graves and J\u00fcrgen Schmidhuber. 2005. Framewise phoneme classification with bidirectional LSTM and other neural network architectures. Neural networks 18, 5--6 (2005), 602--610."},{"key":"e_1_3_2_1_7_1","volume-title":"Tackling Structured Knowledge Extraction from Polymer Nanocomposite Literature as an NER\/RE Task with seq2seq. Integrating Materials and Manufacturing Innovation","author":"Hu Bingyin","year":"2024","unstructured":"Bingyin Hu, Anqi Lin, and L Catherine Brinson. 2024. Tackling Structured Knowledge Extraction from Polymer Nanocomposite Literature as an NER\/RE Task with seq2seq. Integrating Materials and Manufacturing Innovation (2024), 1--13."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2024.3394778"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-024-00874-5"},{"key":"e_1_3_2_1_10_1","volume-title":"Hannaneh Hajishirzi, and Iz Beltagy.","author":"Jain Sarthak","year":"2020","unstructured":"Sarthak Jain, Madeleine Van Zuylen, Hannaneh Hajishirzi, and Iz Beltagy. 2020. SciREX: A challenge dataset for document-level information extraction. arXiv preprint arXiv:2005.00512 (2020)."},{"key":"e_1_3_2_1_11_1","volume-title":"A new entity extraction method based on machine reading comprehension. arXiv preprint arXiv:2108.06444","author":"Jiang Xiaobo","year":"2021","unstructured":"Xiaobo Jiang, Kun He, Jiajun He, and Guangyu Yan. 2021. A new entity extraction method based on machine reading comprehension. arXiv preprint arXiv:2108.06444 (2021)."},{"key":"e_1_3_2_1_12_1","first-page":"98","article-title":"Chinese Named Entity Recognition Based on Contrastive Learning","volume":"12","author":"Jiang Zhouyu","year":"2023","unstructured":"Zhouyu Jiang, Lu Xiang, Xiaomian Kang, and Chengqing Zong. 2023. Chinese Named Entity Recognition Based on Contrastive Learning. Journal of Chinese Information Processing 12 (2023), 98--105. [In Chinese].","journal-title":"Journal of Chinese Information Processing"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00300"},{"key":"e_1_3_2_1_14_1","volume-title":"Icml","volume":"1","author":"Lafferty John","year":"2001","unstructured":"John Lafferty, Andrew McCallum, Fernando Pereira, et al. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Icml, Vol. 1. Williamstown, MA, 3."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i10.21344"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1108\/EL-10-2020-0301"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32236-6_72"},{"key":"e_1_3_2_1_19_1","volume-title":"A unified MRC framework for named entity recognition. arXiv preprint arXiv:1910.11476","author":"Li Xiaoya","year":"2019","unstructured":"Xiaoya Li, Jingrong Feng, Yuxian Meng, Qinghong Han, Fei Wu, and Jiwei Li. 2019. A unified MRC framework for named entity recognition. arXiv preprint arXiv:1910.11476 (2019)."},{"key":"e_1_3_2_1_20_1","volume-title":"Biomedical named-entity recognition by hierarchically fusing biobert representations and deep contextual-level word-embedding. In 2020 International joint conference on neural networks (IJCNN)","author":"Naseem Usman","unstructured":"Usman Naseem, Katarzyna Musial, Peter Eklund, and Mukesh Prasad. 2020. Biomedical named-entity recognition by hierarchically fusing biobert representations and deep contextual-level word-embedding. In 2020 International joint conference on neural networks (IJCNN). IEEE, 1--8."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bts183"},{"key":"e_1_3_2_1_22_1","volume-title":"Innovative agricultural ontology construction using NLP methodologies and graph neural network. Engineering Science and Technology, an International Journal 52","author":"Saravanan Krithikha Sanju","year":"2024","unstructured":"Krithikha Sanju Saravanan and Velammal Bhagavathiappan. 2024. Innovative agricultural ontology construction using NLP methodologies and graph neural network. Engineering Science and Technology, an International Journal 52 (2024), 101675."},{"key":"e_1_3_2_1_23_1","volume-title":"Markus Hagenbuchner, and Gabriele Monfardini.","author":"Scarselli Franco","year":"2008","unstructured":"Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. 2008. The graph neural network model. IEEE transactions on neural networks 20, 1 (2008), 61--80."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1088\/1674-4527\/ad3d15"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.16353\/j.cnki.1000-7490.2022.12.025"},{"key":"e_1_3_2_1_26_1","volume-title":"Diffusionner: Boundary diffusion for named entity recognition. arXiv preprint arXiv:2305.13298","author":"Shen Yongliang","year":"2023","unstructured":"Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, and Yueting Zhuang. 2023. Diffusionner: Boundary diffusion for named entity recognition. arXiv preprint arXiv:2305.13298 (2023)."},{"key":"e_1_3_2_1_27_1","volume-title":"Promptner: Prompt locating and typing for named entity recognition. arXiv preprint arXiv:2305.17104","author":"Shen Yongliang","year":"2023","unstructured":"Yongliang Shen, Zeqi Tan, Shuhui Wu, Wenqi Zhang, Rongsheng Zhang, Yadong Xi, Weiming Lu, and Yueting Zhuang. 2023. Promptner: Prompt locating and typing for named entity recognition. arXiv preprint arXiv:2305.17104 (2023)."},{"key":"e_1_3_2_1_28_1","volume-title":"Parallel instance query network for named entity recognition. arXiv preprint arXiv:2203.10545","author":"Shen Yongliang","year":"2022","unstructured":"Yongliang Shen, Xiaobin Wang, Zeqi Tan, Guangwei Xu, Pengjun Xie, Fei Huang, Weiming Lu, and Yueting Zhuang. 2022. Parallel instance query network for named entity recognition. arXiv preprint arXiv:2203.10545 (2022)."},{"key":"e_1_3_2_1_29_1","volume-title":"Prototypical networks for few-shot learning. Advances in neural information processing systems 30","author":"Snell Jake","year":"2017","unstructured":"Jake Snell, Kevin Swersky, and Richard Zemel. 2017. Prototypical networks for few-shot learning. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_30_1","volume-title":"Global pointer: Novel efficient span-based approach for named entity recognition. arXiv preprint arXiv:2208.03054","author":"Su Jianlin","year":"2022","unstructured":"Jianlin Su, Ahmed Murtadha, Shengfeng Pan, Jing Hou, Jun Sun, Wanwei Huang, Bo Wen, and Yunfeng Liu. 2022. Global pointer: Novel efficient span-based approach for named entity recognition. arXiv preprint arXiv:2208.03054 (2022)."},{"key":"e_1_3_2_1_31_1","volume-title":"Proc. sixth message understanding conf.(MUC-6). 317--332","author":"Sundheim Beth M","year":"1995","unstructured":"Beth M Sundheim. 1995. Named entity task definition, version 2.1. In Proc. sixth message understanding conf.(MUC-6). 317--332."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2004.07.019"},{"key":"e_1_3_2_1_33_1","volume-title":"A Boundary Offset Prediction Network for Named Entity Recognition. arXiv preprint arXiv:2310.18349","author":"Tang Minghao","year":"2023","unstructured":"Minghao Tang, Yongquan He, Yongxiu Xu, Hongbo Xu, Wenyuan Zhang, and Yang Lin. 2023. A Boundary Offset Prediction Network for Named Entity Recognition. arXiv preprint arXiv:2310.18349 (2023)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.424"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11192-022-04332-7"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-64861-3_33"},{"key":"e_1_3_2_1_37_1","volume-title":"AI marker-based large-scale AI literature mining. arXiv preprint arXiv:2011.00518","author":"Yao Rujing","year":"2020","unstructured":"Rujing Yao, Yingchun Ye, Ji Zhang, Shuxiao Li, and Ou Wu. 2020. AI marker-based large-scale AI literature mining. arXiv preprint arXiv:2011.00518 (2020)."},{"key":"e_1_3_2_1_38_1","volume-title":"A study on deep neural networks framework. In 2016 IEEE advanced information management, communicates, electronic and automation control conference (IMCEC)","author":"Yi Huang","unstructured":"Huang Yi, Sun Shiyu, Duan Xiusheng, and Chen Zhigang. 2016. A study on deep neural networks framework. In 2016 IEEE advanced information management, communicates, electronic and automation control conference (IMCEC). IEEE, 1519--1522."},{"key":"e_1_3_2_1_39_1","volume-title":"Analyzing research diversity of scholars based on multi-dimensional calculation of knowledge entities. Scientometrics","author":"Yu Chao","year":"2023","unstructured":"Chao Yu, Chuhan Wang, Tongyang Zhang, Yi Bu, and Jian Xu. 2023. Analyzing research diversity of scholars based on multi-dimensional calculation of knowledge entities. Scientometrics (2023), 1--30."},{"key":"e_1_3_2_1_40_1","volume-title":"Fusing heterogeneous factors with triaffine mechanism for nested named entity recognition. arXiv preprint arXiv:2110.07480","author":"Yuan Zheng","year":"2021","unstructured":"Zheng Yuan, Chuanqi Tan, Songfang Huang, and Fei Huang. 2021. Fusing heterogeneous factors with triaffine mechanism for nested named entity recognition. arXiv preprint arXiv:2110.07480 (2021)."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2023.103574"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"crossref","unstructured":"Wei Zhang Qinggong Wang Xiangtai Kong Jiacheng Xiong Shengkun Ni Duanhua Cao Buying Niu Mingan Chen Yameng Li Runze Zhang et al. 2024. Fine-tuning large language models for chemical text mining. Chemical Science (2024).","DOI":"10.26434\/chemrxiv-2023-k7ct5-v2"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.2c00359"},{"key":"e_1_3_2_1_44_1","first-page":"12","article-title":"ChatGPT-Based Scientific Paper Entity Recognition: Performance Measurement and Availability Research","volume":"09","author":"Zhang Yingyi","year":"2023","unstructured":"Yingyi Zhang, Chengzhi Zhang, Yi Zhou, and Bikun Chen. 2023. ChatGPT-Based Scientific Paper Entity Recognition: Performance Measurement and Availability Research. Data Analysis and Knowledge Discovery 09 (2023), 12--24. [In Chinese].","journal-title":"Data Analysis and Knowledge Discovery"}],"event":{"name":"JCDL '24: 24th ACM\/IEEE Joint Conference on Digital Libraries","location":"Hong Kong China","acronym":"JCDL '24","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","IEEE TCDL"]},"container-title":["Proceedings of the 24th ACM\/IEEE Joint Conference on Digital Libraries"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3677389.3702584","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3677389.3702584","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:19:07Z","timestamp":1750295947000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3677389.3702584"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,16]]},"references-count":44,"alternative-id":["10.1145\/3677389.3702584","10.1145\/3677389"],"URL":"https:\/\/doi.org\/10.1145\/3677389.3702584","relation":{},"subject":[],"published":{"date-parts":[[2024,12,16]]},"assertion":[{"value":"2025-03-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}