{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T19:50:32Z","timestamp":1759693832380,"version":"3.37.3"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2019,7,22]],"date-time":"2019-07-22T00:00:00Z","timestamp":1563753600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,7,22]],"date-time":"2019-07-22T00:00:00Z","timestamp":1563753600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100005153","name":"China National Funds for Distinguished Young Scientists","doi-asserted-by":"publisher","award":["No.61525205"],"award-info":[{"award-number":["No.61525205"]}],"id":[{"id":"10.13039\/501100005153","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.61672367","No.61672368"],"award-info":[{"award-number":["No.61672367","No.61672368"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The National Key Research and Development Program of China","award":["No.2017YFB1002104"],"award-info":[{"award-number":["No.2017YFB1002104"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1007\/s13042-019-00985-8","type":"journal-article","created":{"date-parts":[[2019,7,22]],"date-time":"2019-07-22T14:03:14Z","timestamp":1563804194000},"page":"449-461","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Interactive learning for joint event and relation extraction"],"prefix":"10.1007","volume":"11","author":[{"given":"Jingli","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0606-3718","authenticated-orcid":false,"given":"Yu","family":"Hong","sequence":"additional","affiliation":[]},{"given":"Wenxuan","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Jianmin","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Min","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,7,22]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Ahn D (2006) The stages of event extraction. In: Proceedings of the workshop on annotating and reasoning about time and events. Association for Computational Linguistics, pp 1\u20138","key":"985_CR1","DOI":"10.3115\/1629235.1629236"},{"doi-asserted-by":"crossref","unstructured":"Chen Y, Liu S, Zhang X, Liu K, Zhao J (2017) Automatically labeled data generation for large scale event extraction. In: Proceedings of the 55th annual meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol 1, pp 409\u2013419","key":"985_CR2","DOI":"10.18653\/v1\/P17-1038"},{"doi-asserted-by":"crossref","unstructured":"Chen Y, Xu L, Liu K, Zeng D, Zhao J, et\u00a0al. (2015) Event extraction via dynamic multi-pooling convolutional neural networks. In: ACL (1), pp 167\u2013176","key":"985_CR3","DOI":"10.3115\/v1\/P15-1017"},{"doi-asserted-by":"crossref","unstructured":"Christopoulou F, Miwa M, Ananiadou S (2018) A walk-based model on entity graphs for relation extraction. In: Proceedings of the 56th annual meeting of the Association for Computational Linguistics (Volume 2: Short Papers), vol 2, pp 81\u201388","key":"985_CR4","DOI":"10.18653\/v1\/P18-2014"},{"doi-asserted-by":"crossref","unstructured":"Collobert R, Weston J (2008) A unified architecture for natural language processing: deep neural networks with multitask learning. In: Proceedings of the 25th international conference on machine learning. ACM, pp 160\u2013167","key":"985_CR5","DOI":"10.1145\/1390156.1390177"},{"unstructured":"Doddington GR, Mitchell A, Przybocki MA, Ramshaw LA, Strassel S, Weischedel RM (2004) The automatic content extraction (ACE) program-tasks, data, and evaluation. In: LREC, vol 2, p 1","key":"985_CR6"},{"doi-asserted-by":"crossref","unstructured":"Feng X, Huang L, Tang D, Ji H, Qin B, Liu T (2016) A language-independent neural network for event detection. In: Proceedings of the 54th annual meeting of the Association for Computational Linguistics (Volume 2: Short Papers), vol 2, pp 66\u201371","key":"985_CR7","DOI":"10.18653\/v1\/P16-2011"},{"unstructured":"He D, Xia Y, Qin T, Wang L, Yu N, Liu T, Ma WY (2016) Dual learning for machine translation. In: Advances in neural information processing systems, pp 820\u2013828","key":"985_CR8"},{"unstructured":"Hong Y, Zhang J, Ma B, Yao J, Zhou G, Zhu Q (2011) Using cross-entity inference to improve event extraction. In: Proceedings of the 49th annual meeting of the Association for Computational Linguistics: human language technologies-volume 1. Association for Computational Linguistics, pp 1127\u20131136","key":"985_CR9"},{"doi-asserted-by":"crossref","unstructured":"Hong Y, Zhou W, Zhou G, Zhu Q, et\u00a0al. (2018) Self-regulation: employing a generative adversarial network to improve event detection. In: Proceedings of the 56th annual meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol 1, pp 515\u2013526","key":"985_CR10","DOI":"10.18653\/v1\/P18-1048"},{"unstructured":"Ji H, Grishman R (2008) Refining event extraction through cross-document inference. In: Proceedings of ACL-08: HLT, pp 254\u2013262","key":"985_CR11"},{"key":"985_CR12","volume-title":"Unsupervised feature selection for relation extraction","author":"C Jinxiu","year":"2005","unstructured":"Jinxiu C, Ji T (2005) Unsupervised feature selection for relation extraction. National University of Singapore, Singapore"},{"doi-asserted-by":"crossref","unstructured":"Li Q, Ji H (2014) Incremental joint extraction of entity mentions and relations. In: Proceedings of the 52nd annual meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol 1, pp 402\u2013412","key":"985_CR13","DOI":"10.3115\/v1\/P14-1038"},{"unstructured":"Li Q, Ji H, Huang L (2013) Joint event extraction via structured prediction with global features. In: ACL (1), pp 73\u201382","key":"985_CR14"},{"unstructured":"Liao S, Grishman R (2010) Using document level cross-event inference to improve event extraction. In: Proceedings of the 48th annual meeting of the Association for Computational Linguistics. Association for Computational Linguistics, pp 789\u2013797","key":"985_CR15"},{"doi-asserted-by":"crossref","unstructured":"Lin Y, Shen S, Liu Z, Luan H, Sun M (2016) Neural relation extraction with selective attention over instances. In: Proceedings of the 54th annual meeting of the Association for Computational Linguistics (Volume 1: Long Papers), vol 1, pp 2124\u20132133","key":"985_CR16","DOI":"10.18653\/v1\/P16-1200"},{"key":"985_CR17","first-page":"1250","volume":"1000","author":"J Liu","year":"2018","unstructured":"Liu J, Chen Y, Liu K, Zhao J (2018) Event detection via gated multilingual attention mechanism. Statistics 1000:1250","journal-title":"Statistics"},{"key":"985_CR18","first-page":"1789","volume":"1","author":"S Liu","year":"2017","unstructured":"Liu S, Chen Y, Liu K, Zhao J (2017) Exploiting argument information to improve event detection via supervised attention mechanisms 1:1789\u20131797","journal-title":"Exploiting argument information to improve event detection via supervised attention mechanisms"},{"unstructured":"Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient estimation of word representations in vector space. \narXiv:1301.3781\n\n (arXiv preprint)","key":"985_CR19"},{"doi-asserted-by":"crossref","unstructured":"Miwa M, Bansal M (2016) End-to-end relation extraction using lstms on sequences and tree structures. \narXiv:1601.00770\n\n (arXiv preprint)","key":"985_CR20","DOI":"10.18653\/v1\/P16-1105"},{"unstructured":"Nguyen T.H, Cho K, Grishman R (2016) Joint event extraction via recurrent neural networks. In: HLT-NAACL, pp 300\u2013309","key":"985_CR21"},{"unstructured":"Nguyen T.H, Grishman R (2015) Event detection and domain adaptation with convolutional neural networks. In: ACL (2), pp 365\u2013371","key":"985_CR22"},{"unstructured":"Pawar S, Bhattacharya P, Palshikar G.K (2016) End-to-end relation extraction using markov logic networks. In: International conference on intelligent text processing and computational linguistics. Springer, pp 535\u2013551","key":"985_CR23"},{"doi-asserted-by":"crossref","unstructured":"Qian L, Zhou G, Kong F, Zhu Q, Qian P (2008) Exploiting constituent dependencies for tree kernel-based semantic relation extraction. In: Proceedings of the 22nd international conference on computational linguistics-volume 1. Association for Computational Linguistics, pp. 697\u2013704","key":"985_CR24","DOI":"10.3115\/1599081.1599169"},{"doi-asserted-by":"crossref","unstructured":"Tang D, Qin B, Liu T (2015) Document modeling with gated recurrent neural network for sentiment classification. In: Proceedings of the 2015 conference on empirical methods in natural language processing, pp 1422\u20131432","key":"985_CR25","DOI":"10.18653\/v1\/D15-1167"},{"unstructured":"Turian J, Ratinov L, Bengio Y (2010) Word representations: a simple and general method for semi-supervised learning. In: Proceedings of the 48th annual meeting of the Association for Computational Linguistics. Association for Computational Linguistics, pp 384\u2013394","key":"985_CR26"},{"unstructured":"Yan X, Mou L, Li G, Chen Y, Peng H, Jin Z (2015) Classifying relations via long short term memory networks along shortest dependency path. \narXiv:1508.03720\n\n (arXiv preprint)","key":"985_CR27"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00985-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-019-00985-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00985-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,7,20]],"date-time":"2020-07-20T23:17:49Z","timestamp":1595287069000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-019-00985-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,22]]},"references-count":27,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,2]]}},"alternative-id":["985"],"URL":"https:\/\/doi.org\/10.1007\/s13042-019-00985-8","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2019,7,22]]},"assertion":[{"value":"15 December 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 July 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}