{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T10:38:57Z","timestamp":1742380737616,"version":"3.37.3"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T00:00:00Z","timestamp":1675728000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T00:00:00Z","timestamp":1675728000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Key Research and Development Program of China","award":["2021YFB2700200"],"award-info":[{"award-number":["2021YFB2700200"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772151","62106059"],"award-info":[{"award-number":["61772151","62106059"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s13042-022-01760-y","type":"journal-article","created":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T04:47:30Z","timestamp":1675745250000},"page":"79-95","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Label graph augmented soft cascade decoding model for overlapping event extraction"],"prefix":"10.1007","volume":"15","author":[{"given":"Yiming","family":"Hei","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0179-2364","authenticated-orcid":false,"given":"Lihong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawei","family":"Sheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianwei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shu","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,2,7]]},"reference":[{"issue":"1","key":"1760_CR1","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1145\/234173.234209","volume":"39","author":"J Cowie","year":"1996","unstructured":"Cowie J, Lehnert W (1996) Information extraction. Commun ACM 39(1):80\u201391","journal-title":"Commun ACM"},{"key":"1760_CR2","doi-asserted-by":"crossref","unstructured":"Li Q, Li J, Sheng J, Cui S, Wu J, Hei Y, Peng H, Guo S, Wang L, Beheshti A, Yu PS (2021) A Survey on Deep Learning Event Extraction: Approaches and Applications. CoRR. arXiv:2107.02126","DOI":"10.1109\/TNNLS.2022.3213168"},{"key":"1760_CR3","doi-asserted-by":"crossref","unstructured":"Zhang H, Liu X, Pan H, Song Y, Leung CW (2020) ASER: a large-scale eventuality knowledge graph. In: Proceedings of the 29th international world wide web conference, WWW, April 20\u201324, 2020, pp 201\u2013211","DOI":"10.1145\/3366423.3380107"},{"key":"1760_CR4","doi-asserted-by":"crossref","unstructured":"Du L, Ding X, Liu T, Qin B (2021) Learning event graph knowledge for abductive reasoning. In: Proceedings of the 59th annual meeting of the Association for Computational Linguistics and the 11th international joint conference on natural language processing, ACL, August 1\u20136, 2021, pp 5181\u20135190","DOI":"10.18653\/v1\/2021.acl-long.403"},{"key":"1760_CR5","doi-asserted-by":"crossref","unstructured":"Du L, Ding X, Xiong K, Liu T, Qin B (2021) Excar: Event graph knowledge enhanced explainable causal reasoning. In: Proceedings of the 59th annual meeting of the Association for Computational Linguistics and the 11th international joint conference on natural language processing, ACL, August 1\u20136, 2021, pp 2354\u20132363","DOI":"10.18653\/v1\/2021.acl-long.183"},{"key":"1760_CR6","doi-asserted-by":"crossref","unstructured":"Peng H, Li J, Gong Q, Song Y, Ning Y, Lai K, Yu PS (2019) Fine-grained event categorization with heterogeneous graph convolutional networks. In: Proceedings of the 28th international joint conference on artificial intelligence, IJCAI, August 10\u201316, 2019, pp 3238\u20133245","DOI":"10.24963\/ijcai.2019\/449"},{"issue":"5","key":"1760_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3447585","volume":"15","author":"H Peng","year":"2021","unstructured":"Peng H, Li J, Song Y, Yang R, Ranjan R, Yu PS, He L (2021) Streaming social event detection and evolution discovery in heterogeneous information networks. ACM Trans Knowl Discov Data (TKDD) 15(5):1\u201333","journal-title":"ACM Trans Knowl Discov Data (TKDD)"},{"key":"1760_CR8","doi-asserted-by":"crossref","unstructured":"Peng H, Zhang R, Li S, Cao Y, Pan S, Yu P (2023) Reinforced, incremental and cross-lingual event detection from social messages. IEEE Trans Pattern Anal Mach Intell (TPAMI) 45(1): 980\u2013998","DOI":"10.1109\/TPAMI.2022.3144993"},{"key":"1760_CR9","doi-asserted-by":"crossref","unstructured":"Ren J, Jiang L, Peng H, Liu Z, Wu J, Yu PS (2022) Evidential temporal-aware graph-based social event detection via Dempster\u2013Shafer theory. In: International conference on web services, ICWS 2022","DOI":"10.1109\/ICWS55610.2022.00055"},{"key":"1760_CR10","unstructured":"Ren J, Peng H, Jiang L, Wu J, Tong Y, Wang L, Bai X, Wang B, Yang Q (2021) Transferring knowledge distillation for multilingual social event detection. CoRR. arXiv:2108.03084"},{"key":"1760_CR11","doi-asserted-by":"crossref","unstructured":"Ren J, Jiang L, Peng H, Cao Y, Wu J, Yu PS, He L (2022) From known to unknown: quality-aware self-improving graph neural network for open set social event detection. In: Proceedings of the 31th ACM international conference on information and knowledge management, CIKM 2022, Georgia, USA, October 17\u201321, 2022","DOI":"10.1145\/3511808.3557329"},{"key":"1760_CR12","doi-asserted-by":"crossref","unstructured":"Lin X, Cao J, Zhang P, Zhou C, Li Z, Wu J, Wang B (2021) Disentangled deep multivariate Hawkes process for learning event sequences. In: IEEE international conference on data mining, ICDM 2021, Auckland, New Zealand, December 7\u201310, 2021, pp 360\u2013369","DOI":"10.1109\/ICDM51629.2021.00047"},{"key":"1760_CR13","unstructured":"Deng S, Rangwala H, Ning Y (2021) Causal knowledge guided societal event forecasting. CoRR. arXiv:2112.05695"},{"key":"1760_CR14","doi-asserted-by":"crossref","unstructured":"Liu C, Zhou C, Wu J, Xie H, Hu Y, Guo L (2017) CPMF: a collective pairwise matrix factorization model for upcoming event recommendation. In: 2017 International joint conference on neural networks, IJCNN 2017, Anchorage, AK, USA, May 14\u201319, 2017, pp 1532\u20131539","DOI":"10.1109\/IJCNN.2017.7966033"},{"key":"1760_CR15","doi-asserted-by":"crossref","unstructured":"Gao L, Wu J, Qiao Z, Zhou C, Yang H, Hu Y (2016) Collaborative social group influence for event recommendation. In: Proceedings of the 25th ACM international conference on information and knowledge management, CIKM 2016, Indianapolis, IN, USA, October 24\u201328, 2016, pp 1941\u20131944","DOI":"10.1145\/2983323.2983879"},{"key":"1760_CR16","doi-asserted-by":"crossref","unstructured":"Chen Y, Xu L, Liu K, Zeng D, Zhao J (2015) Event extraction via dynamic multi-pooling convolutional neural networks. In: Proceedings of the 53rd annual meeting of the Association for Computational Linguistics, ACL July 26\u201331, 2015, pp 167\u2013176","DOI":"10.3115\/v1\/P15-1017"},{"key":"1760_CR17","doi-asserted-by":"crossref","unstructured":"Sha L, Qian F, Chang B, Sui Z (2018) Jointly extracting event triggers and arguments by dependency-bridge RNN and tensor-based argument interaction. In: Proceedings of the 32th AAAI conference on artificial intelligence, AAAI, February 2\u20137, 2018, pp 5916\u20135923","DOI":"10.1609\/aaai.v32i1.12034"},{"key":"1760_CR18","doi-asserted-by":"crossref","unstructured":"Chen Y, Xu L, Liu K, Zeng D, Zhao J (2015) Event extraction via dynamic multi-pooling convolutional neural networks. In: Proceedings of the 53rd annual meeting of the Association for Computational Linguistics, ACL, July 26\u201331, 2015, pp 167\u2013176","DOI":"10.3115\/v1\/P15-1017"},{"key":"1760_CR19","doi-asserted-by":"crossref","unstructured":"Sha L, Liu J, Lin C, Li S, Chang B, Sui Z (2016) RBPB: regularization-based pattern balancing method for event extraction. In: Proceedings of the 54th annual meeting of the Association for Computational Linguistics, ACL, August 7\u201312, 2016","DOI":"10.18653\/v1\/P16-1116"},{"key":"1760_CR20","doi-asserted-by":"crossref","unstructured":"Yang S, Feng D, Qiao L, Kan Z, Li D (2019) Exploring pre-trained language models for event extraction and generation. In: Proceedings of the 57th conference of the Association for Computational Linguistics, ACL, July 28\u2013August 2, 2019, pp 5284\u20135294","DOI":"10.18653\/v1\/P19-1522"},{"key":"1760_CR21","doi-asserted-by":"crossref","unstructured":"Huang L, Ji H, Cho K, Dagan I, Riedel S, Voss CR (2018) Zero-shot transfer learning for event extraction. In: Proceedings of the 56th annual meeting of the Association for Computational Linguistics, ACL, July 15\u201320, 2018, pp 2160\u20132170","DOI":"10.18653\/v1\/P18-1201"},{"key":"1760_CR22","doi-asserted-by":"crossref","unstructured":"Li F, Peng W, Chen Y, Wang Q, Pan L, Lyu Y, Zhu Y (2020) Event extraction as multi-turn question answering. In: Proceedings of the 2020 conference on empirical methods in natural language processing, EMNLP, November 16\u201320, 2020, pp 829\u2013838","DOI":"10.18653\/v1\/2020.findings-emnlp.73"},{"key":"1760_CR23","doi-asserted-by":"crossref","unstructured":"Nguyen TH, Cho K, Grishman R (2016) Joint event extraction via recurrent neural networks. In: Proceedings of the 2016 conference of the North American chapter of the Association for Computational Linguistics, NAACL, June 12\u201317, 2016, pp 300\u2013309","DOI":"10.18653\/v1\/N16-1034"},{"key":"1760_CR24","doi-asserted-by":"crossref","unstructured":"Nguyen TM, Nguyen TH (2019) One for all: neural joint modeling of entities and events. In: Proceedings of the 33th AAAI conference on artificial intelligence, AAAI, January 27\u2013February 1, 2019, pp 6851\u20136858","DOI":"10.1609\/aaai.v33i01.33016851"},{"key":"1760_CR25","doi-asserted-by":"crossref","unstructured":"Wadden D, Wennberg U, Luan Y, Hajishirzi H (2019) Entity, relation, and event extraction with contextualized span representations. In: Proceedings of the 2019 conference on empirical methods in natural language processing, EMNLP, November 3\u20137, 2019, pp 5783\u20135788","DOI":"10.18653\/v1\/D19-1585"},{"key":"1760_CR26","doi-asserted-by":"crossref","unstructured":"Lu Y, Lin H, Xu J, Han X, Tang J, Li A, Sun L, Liao M, Chen S (2021) Text2event: controllable sequence-to-structure generation for end-to-end event extraction. In: Proceedings of the 59th annual meeting of the Association for Computational Linguistics ACL, August 1\u20136, 2021, pp 2795\u20132806","DOI":"10.18653\/v1\/2021.acl-long.217"},{"key":"1760_CR27","doi-asserted-by":"crossref","unstructured":"Sheng J, Guo S, Yu B, Li Q, Hei Y, Wang L, Liu T, Xu H (2021) CasEE: a joint learning framework with cascade decoding for overlapping event extraction. In: Proceedings of the 59th conference of the Association for Computational Linguistics, ACL, August 1\u20136, 2021, pp 164\u2013174","DOI":"10.18653\/v1\/2021.findings-acl.14"},{"key":"1760_CR28","doi-asserted-by":"crossref","unstructured":"Xu N, Xie H, Zhao D (2020) A novel joint framework for multiple Chinese events extraction. In: Sun M, Li S, Zhang Y, Liu Y, He S, Rao G (eds) Proceedings of the 19th Chinese computational linguistics and natural language processing, CCL, October 30\u2013November 1, 2020, vol 12522, pp 174\u2013183","DOI":"10.1007\/978-3-030-63031-7_13"},{"key":"1760_CR29","unstructured":"Bengio S, Vinyals O, Jaitly N, Shazeer N (2015) Scheduled sampling for sequence prediction with recurrent neural networks. In: Proceedings of the 28th annual conference on neural information processing systems, NIPS , December 7\u201312, 2015, pp 1171\u20131179"},{"key":"1760_CR30","doi-asserted-by":"crossref","unstructured":"Zhou Y, Chen Y, Zhao J, Wu Y, Xu J, Li J (2021) What the role is vs. what plays the role: semi-supervised event argument extraction via dual question answering. In: Proceedings of the 35th AAAI conference on artificial intelligence, AAAI, February 2\u20139, 2021, pp 14638\u201314646","DOI":"10.1609\/aaai.v35i16.17720"},{"key":"1760_CR31","unstructured":"Doddington GR, Mitchell A, Przybocki MA, Ramshaw LA, Strassel SM, Weischedel RM (2004) The automatic content extraction (ACE) program\u2014tasks, data, and evaluation. In: Proceedings of the 4th international conference on language resources and evaluation, LREC, May 26\u201328, 2004"},{"key":"1760_CR32","unstructured":"Huang R, Riloff E (2012) Modeling textual cohesion for event extraction. In: Proceedings of the 26th AAAI conference on artificial intelligence, AAAI, July 22\u201326, 2012"},{"key":"1760_CR33","unstructured":"Miwa M, Thompson P, Korkontzelos I, Ananiadou S (2014) Comparable study of event extraction in newswire and biomedical domains. In: Proceedings of the 25th international conference on computational linguistics, COLING, August 23\u201329, 2014, pp 2270\u20132279"},{"key":"1760_CR34","doi-asserted-by":"crossref","unstructured":"Chen Y, Liu S, He S, Liu K, Zhao J (2016) Event extraction via bidirectional long short-term memory tensor neural networks. In: Proceedings of the 15th Chinese computational linguistics and natural language processing, CCL, October 15\u201316, 2016, vol 10035, pp 190\u2013203","DOI":"10.1007\/978-3-319-47674-2_17"},{"key":"1760_CR35","doi-asserted-by":"crossref","unstructured":"Venugopal D, Chen C, Gogate V, Ng V (2014) Relieving the computational bottleneck: joint inference for event extraction with high-dimensional features. In: Proceedings of the 2014 conference on empirical methods in natural language processing, EMNLP, October 25\u201329, 2014, pp 831\u2013843","DOI":"10.3115\/v1\/D14-1090"},{"key":"1760_CR36","doi-asserted-by":"crossref","unstructured":"Yang B, Mitchell TM (2016) Joint extraction of events and entities within a document context. In: Proceedings of the 2016 conference of the North American chapter of the Association for Computational Linguistics, NAACL, June 12\u201317, 2016, pp 289\u2013299","DOI":"10.18653\/v1\/N16-1033"},{"key":"1760_CR37","doi-asserted-by":"crossref","unstructured":"Luo Y, Zhao H (2020) Bipartite flat-graph network for nested named entity recognition. In: Proceedings of the 58th annual meeting of the Association for Computational Linguistics, ACL, July 5\u201310, 2020, pp 6408\u20136418","DOI":"10.18653\/v1\/2020.acl-main.571"},{"key":"1760_CR38","doi-asserted-by":"crossref","unstructured":"Li J, Fei H, Liu J, Wu S, Zhang M, Teng C, Ji D, Li F (2022) Unified named entity recognition as word-word relation classification. Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI, February 22 - March 1, 2022, pp 10965-10973","DOI":"10.1609\/aaai.v36i10.21344"},{"key":"1760_CR39","doi-asserted-by":"crossref","unstructured":"Zeng X, Zeng D, He S, Liu K, Zhao J (2018) Extracting relational facts by an end-to-end neural model with copy mechanism. In: Proceedings of the 56th annual meeting of the Association for Computational Linguistics, ACL, July 15\u201320, 2018, pp 506\u2013514","DOI":"10.18653\/v1\/P18-1047"},{"key":"1760_CR40","doi-asserted-by":"crossref","unstructured":"Wei Z, Su J, Wang Y, Tian Y, Chang Y (2020) A novel cascade binary tagging framework for relational triple extraction. In: Proceedings of the 58th annual meeting of the Association for Computational Linguistics, ACL, July 5\u201310, 2020, pp 1476\u20131488","DOI":"10.18653\/v1\/2020.acl-main.136"},{"issue":"1","key":"1760_CR41","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/TNNLS.2020.2978386","volume":"32","author":"Z Wu","year":"2021","unstructured":"Wu Z, Pan S, Chen F, Long G, Zhang C, Yu PS (2021) A comprehensive survey on graph neural networks. IEEE Trans Neural Netw Learn Syst (TNNLS) 32(1):4\u201324","journal-title":"IEEE Trans Neural Netw Learn Syst (TNNLS)"},{"key":"1760_CR42","unstructured":"Kipf TN, Welling M (2017) Semi-supervised classification with graph convolutional networks. In: Proceedings of the 5th international conference on learning representations, ICLR, April 24\u201326, 2017, pp 1\u201314"},{"key":"1760_CR43","unstructured":"Devlin J, Chang M, Lee K, Toutanova K (2019) 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, NAACL, June 2\u20137, 2019, pp 4171\u20134186"},{"key":"1760_CR44","doi-asserted-by":"crossref","unstructured":"Liu S, Li Y, Zhang F, Yang T, Zhou X (2019) Event detection without triggers. In: Proceedings of the 2019 conference of the North American chapter of the Association for Computational Linguistics, NAACL, June 2\u20137, 2019, pp 735\u2013744","DOI":"10.18653\/v1\/N19-1080"},{"key":"1760_CR45","doi-asserted-by":"crossref","unstructured":"Yu B, Zhang Z, Sheng J, Liu T, Wang Y, Wang Y, Wang B (2021) Semi-open information extraction. In: Proceedings of the 30th international world wide web conference, WWW, April 19\u201323, 2021, pp 1661\u20131672","DOI":"10.1145\/3442381.3450029"},{"key":"1760_CR46","unstructured":"Lafferty JD, McCallum A, Pereira FCN (2001) Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proceedings of the eighteenth international conference on machine learning ICML, June 28\u2013July 1, 2001, pp 282\u2013289"},{"key":"1760_CR47","doi-asserted-by":"crossref","unstructured":"Du X, Cardie C (2020) Document-level event role filler extraction using multi-granularity contextualized encoding. In: Proceedings of the 58th annual meeting of the Association for Computational Linguistics, ACL, July 5\u201310, 2020, pp 8010\u20138020","DOI":"10.18653\/v1\/2020.acl-main.714"},{"issue":"2","key":"1760_CR48","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1162\/dint_a_00014","volume":"1","author":"T Zhang","year":"2019","unstructured":"Zhang T, Ji H, Sil A (2019) Joint entity and event extraction with generative adversarial imitation learning. Data Intell 1(2):99\u2013120","journal-title":"Data Intell"},{"key":"1760_CR49","doi-asserted-by":"crossref","unstructured":"Du X, Cardie C (2020) Event extraction by answering (almost) natural questions. In: Proceedings of the 2020 conference on empirical methods in natural language processing, EMNLP, November 16\u201320, 2020, pp 671\u2013683","DOI":"10.18653\/v1\/2020.emnlp-main.49"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-022-01760-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-022-01760-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-022-01760-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,6]],"date-time":"2024-01-06T08:20:44Z","timestamp":1704529244000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-022-01760-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,7]]},"references-count":49,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["1760"],"URL":"https:\/\/doi.org\/10.1007\/s13042-022-01760-y","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2023,2,7]]},"assertion":[{"value":"5 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 December 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}