{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T15:26:05Z","timestamp":1774538765475,"version":"3.50.1"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62433002"],"award-info":[{"award-number":["62433002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72301010"],"award-info":[{"award-number":["72301010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Project of Construction and Support for High-Level Innovative Teams of Beijing Municipal Institutions","award":["BPHR20220104"],"award-info":[{"award-number":["BPHR20220104"]}]},{"name":"Beijing Scholars Program","award":["099"],"award-info":[{"award-number":["099"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3546963","type":"journal-article","created":{"date-parts":[[2025,3,3]],"date-time":"2025-03-03T18:36:06Z","timestamp":1741026966000},"page":"40169-40184","source":"Crossref","is-referenced-by-count":1,"title":["Event Type and Relationship Extraction Based on Dependent Syntactic Semantic Augmented Graph Networks"],"prefix":"10.1109","volume":"13","author":[{"given":"Min","family":"Zuo","sequence":"first","affiliation":[{"name":"National Engineering Research Centre for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zexi","family":"Song","sequence":"additional","affiliation":[{"name":"National Engineering Research Centre for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9225-7660","authenticated-orcid":false,"given":"Qingchuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Engineering Research Centre for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueheng","family":"Liu","sequence":"additional","affiliation":[{"name":"Beijing Academy of TCM Beauty Supplements Company Ltd., Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Di","family":"Wu","sequence":"additional","affiliation":[{"name":"Beijing Academy of TCM Beauty Supplements Company Ltd., Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1310-033X","authenticated-orcid":false,"given":"Yuanyuan","family":"Cai","sequence":"additional","affiliation":[{"name":"National Engineering Research Centre for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"123483","DOI":"10.1109\/ACCESS.2020.3004378","article-title":"Event arguments extraction via dilate gated convolutional neural network with enhanced local features","volume":"8","author":"Kan","year":"2020","journal-title":"IEEE Access"},{"key":"ref2","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2023.101919","article-title":"Knowledge-enhanced event relation extraction via event ontology prompt","volume":"100","author":"Zhuang","year":"2023","journal-title":"Inf. Fusion"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"25001","DOI":"10.1109\/ACCESS.2019.2900124","article-title":"Joint event extraction based on hierarchical event schemas from FrameNet","volume":"7","author":"Li","year":"2019","journal-title":"IEEE Access"},{"key":"ref4","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4614-5311-6_3","article-title":"Automatic extraction of events from open source text for predictive forecasting","volume-title":"Handbook of Computational Approaches to Counterterrorism","author":"Boschee","year":"2013"},{"key":"ref5","first-page":"1273","article-title":"TEDAS: A Twitter-based event detection and analysis system","volume-title":"Proc. IEEE 28th Int. Conf. Data Eng.","author":"Li"},{"issue":"12","key":"ref6","doi-asserted-by":"crossref","first-page":"4393","DOI":"10.1007\/s13042-023-01900-y","article-title":"General fine-grained event detection based on fusion of multi-information representation and attention mechanism","volume":"14","author":"He","year":"2023","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref7","doi-asserted-by":"crossref","first-page":"171435","DOI":"10.1109\/ACCESS.2020.3024872","article-title":"Graph convolution over multiple latent context-aware graph structures for event detection","volume":"8","author":"Li","year":"2020","journal-title":"IEEE Access"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.artmed.2017.10.003","article-title":"SSEL-ADE: A semi-supervised ensemble learning framework for extracting adverse drug events from social media","volume":"84","author":"Liu","year":"2018","journal-title":"Artif. Intell. Med."},{"key":"ref9","article-title":"Joint reasoning for temporal and causal relations","author":"Ning","year":"2019","journal-title":"arXiv:1906.04941"},{"key":"ref10","first-page":"3558","article-title":"LearnDA: Learnable knowledge-guided data augmentation for event causality identification","volume-title":"Proc. Annu. Meeting Assoc. Comput. Linguistics","author":"Zuo"},{"issue":"1","key":"ref11","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1080\/09540091.2020.1753172","article-title":"A community partitioning algorithm based on network enhancement","volume":"33","author":"Hu","year":"2021","journal-title":"Connection Sci."},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.129"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.220"},{"key":"ref14","first-page":"167","article-title":"Event extraction via dynamic multi-pooling convolutional neural networks","volume-title":"Proc. Annu. Meeting Assoc. Comput. Linguistics","author":"Chen"},{"key":"ref15","first-page":"300","article-title":"Joint event extraction via recurrent neural networks","volume-title":"Proc. North Amer. Chapter Assoc. Comput. Linguistics, Human Lang. Technol.","author":"Nguyen"},{"issue":"3","key":"ref16","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1162\/dint_a_00103","article-title":"A prior information enhanced extraction framework for document-level financial event extraction","volume":"3","author":"Wang","year":"2021","journal-title":"Data Intell."},{"key":"ref17","doi-asserted-by":"crossref","first-page":"1549","DOI":"10.1109\/TBDATA.2023.3291563","article-title":"Event extraction by associating event types and argument roles","volume":"9","author":"Li","year":"2021","journal-title":"IEEE Trans. Big Data"},{"issue":"6","key":"ref18","doi-asserted-by":"crossref","first-page":"6554","DOI":"10.1007\/s10489-022-03598-x","article-title":"A syntactic distance sensitive neural network for event argument extraction","volume":"53","author":"Dai","year":"2023","journal-title":"Applied Intelligence"},{"issue":"13","key":"ref19","doi-asserted-by":"crossref","first-page":"7942","DOI":"10.3390\/app13137942","article-title":"An open-domain event extraction method incorporating semantic and dependent syntactic information","volume":"13","author":"He","year":"2023","journal-title":"Appl. Sci."},{"issue":"15","key":"ref20","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2024.e34057","article-title":"Biomedical event argument detection method based on multi-feature fusion and question-answer paradigm","volume":"10","author":"Tian","year":"2024","journal-title":"Heliyon"},{"key":"ref21","first-page":"190","article-title":"Joint prior relation enhancement and non-autoregressive decoding for document-level event extraction","volume-title":"Proc. Int. Conf. Intell. Comput.","author":"Kang"},{"issue":"7","key":"ref22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3663567","article-title":"Enhancing Chinese event extraction with event trigger structures","volume":"23","author":"Li","year":"2024","journal-title":"ACM Trans. Asian Low-Resource Lang. Inf. Process."},{"issue":"2","key":"ref23","doi-asserted-by":"crossref","first-page":"547","DOI":"10.26599\/BDMA.2023.9020036","article-title":"KeyEE: Enhancing low-resource generative event extraction with auxiliary keyword sub-prompt","volume":"7","author":"Duan","year":"2024","journal-title":"Big Data Mining Analytics"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CCDC.2011.5968467"},{"issue":"6","key":"ref25","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2020.102319","article-title":"Extracting temporal and causal relations based on event networks","volume":"57","author":"Vo","year":"2020","journal-title":"Inf. Process. Manage."},{"issue":"1","key":"ref26","doi-asserted-by":"crossref","first-page":"79","DOI":"10.26599\/TST.2020.9010063","article-title":"Event temporal relation extraction with attention mechanism and graph neural network","volume":"27","author":"Xu","year":"2022","journal-title":"Tsinghua Sci. Technol."},{"key":"ref27","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1016\/j.eswa.2018.08.009","article-title":"Knowledge-oriented convolutional neural network for causal relation extraction from natural language texts","volume":"115","author":"Li","year":"2019","journal-title":"Exp. Syst. Appl."},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.60"},{"key":"ref29","first-page":"1","article-title":"Document-level event temporal relation extraction on global and local cues","volume-title":"Proc. Int. Joint Conf. Neural Netw. (IJCNN)","author":"Li"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.ins.2023.01.143","article-title":"CFERE: Multi-type Chinese financial event relation extraction","volume":"630","author":"Wan","year":"2023","journal-title":"Inf. Sci."},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1609.02907"},{"issue":"2","key":"ref32","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1109\/JAS.2021.1004311","article-title":"Sampling methods for efficient training of graph convolutional networks: A survey","volume":"9","author":"Liu","year":"2022","journal-title":"IEEE\/CAA J. Autom. Sinica"},{"key":"ref33","first-page":"4762","article-title":"COMET: Commonsense transformers for automatic knowledge graph construction","volume-title":"Proc. Annu. Meeting Assoc. Comput. Linguistics","author":"Bosselut"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1128"},{"issue":"9","key":"ref35","doi-asserted-by":"crossref","first-page":"11002","DOI":"10.1109\/TII.2024.3397401","article-title":"Multiscale channel attention-driven graph dynamic fusion learning method for robust fault diagnosis","volume":"20","author":"Zhang","year":"2024","journal-title":"IEEE Trans. Ind. Informat."},{"key":"ref36","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2024.111761","article-title":"Adaptive convergent visibility graph network: An interpretable method for intelligent rolling bearing diagnosis","volume":"222","author":"Li","year":"2025","journal-title":"Mech. Syst. Signal Process."},{"key":"ref37","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2022.109615","article-title":"A novel unsupervised directed hierarchical graph network with clustering representation for intelligent fault diagnosis of machines","volume":"183","author":"Zhao","year":"2023","journal-title":"Mech. Syst. Signal Process."},{"key":"ref38","first-page":"1409","article-title":"GraphRel: Modeling text as relational graphs for joint entity and relation extraction","volume-title":"Proc. Annu. Meeting Assoc. Comput. Linguistics","author":"Fu"},{"key":"ref39","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106492","article-title":"Joint event extraction along shortest dependency paths using graph convolutional networks","volume":"210","author":"Balali","year":"2020","journal-title":"Knowl.-Based Syst."},{"issue":"4","key":"ref40","doi-asserted-by":"crossref","first-page":"719","DOI":"10.26599\/TST.2021.9010056","article-title":"MHGCN: Multiview highway graph convolutional network for cross-lingual entity alignment","volume":"27","author":"Gao","year":"2022","journal-title":"Tsinghua Sci. Technol."},{"key":"ref41","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106292","article-title":"SK-GCN: Modeling syntax and knowledge via graph convolutional network for aspect-level sentiment classification","volume":"205","author":"Zhou","year":"2020","journal-title":"Knowl.-Based Syst."},{"issue":"1","key":"ref42","doi-asserted-by":"crossref","first-page":"1785","DOI":"10.1080\/09540091.2022.2080183","article-title":"GP-GCN: Global features of orthogonal projection and local dependency fused graph convolutional networks for aspect-level sentiment classification","volume":"34","author":"Wei","year":"2022","journal-title":"Connection Sci."},{"issue":"24","key":"ref43","doi-asserted-by":"crossref","first-page":"13815","DOI":"10.1007\/s00500-022-07370-8","article-title":"Causality extraction model based on two-stage GCN","volume":"26","author":"Zhu","year":"2022","journal-title":"Soft Comput."},{"issue":"22","key":"ref44","doi-asserted-by":"crossref","first-page":"17369","DOI":"10.1007\/s00500-023-08882-7","article-title":"Biomedical event causal relation extraction based on a knowledge-guided hierarchical graph network","volume":"27","author":"Zhang","year":"2023","journal-title":"Soft Comput."},{"key":"ref45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.heliyon.2023.e19265","article-title":"Using transfer learning-based causality extraction to mine latent factors for Sj\u00f6gren\u2019s syndrome from biomedical literature","volume":"9","author":"VanSchaik","year":"2023","journal-title":"Heliyon"},{"issue":"4","key":"ref46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3643885","article-title":"Token-event-role structure-based multi-channel document-level event extraction","volume":"42","author":"Wan","year":"2024","journal-title":"ACM Trans. Inf. Syst."},{"key":"ref47","article-title":"Deep biaffine attention for neural dependency parsing","author":"Dozat","year":"2016","journal-title":"arXiv:1611.01734"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1454"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.466"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.701"},{"key":"ref51","first-page":"998","article-title":"Adversarial training for weakly supervised event detection","volume-title":"Proc. Conf. North Amer. Chapter Assoc. Comput. Linguistics, Human Language Technol.","volume":"1","author":"Wang"},{"key":"ref52","first-page":"4829","article-title":"MLBiNet: A cross-sentence collective event detection network","volume-title":"Proc. Annu. Meeting Assoc. Comput. Linguistics","author":"Lou"},{"key":"ref53","article-title":"Structured prediction as translation between augmented natural languages","author":"Paolini","year":"2021","journal-title":"arXiv:2101.05779"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.217"},{"key":"ref55","first-page":"1122","article-title":"CorED: Incorporating type-level and instance-level correlations for fine-grained event detection","volume-title":"Proc. 45th Int. ACM SIGIR Conf. Res. Develop. Inf. Retr.","author":"Sheng"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.acl-long.21"},{"key":"ref57","first-page":"1487","article-title":"Hyperspherical prototype networks","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Mettes"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/10908850.pdf?arnumber=10908850","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T04:54:56Z","timestamp":1741668896000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10908850\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":57,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3546963","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}