{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:06:32Z","timestamp":1760709992581,"version":"3.37.3"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2019,8,29]],"date-time":"2019-08-29T00:00:00Z","timestamp":1567036800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,8,29]],"date-time":"2019-08-29T00:00:00Z","timestamp":1567036800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"crossref","award":["2017YFB0803302","2016QY03D0602"],"award-info":[{"award-number":["2017YFB0803302","2016QY03D0602"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61751201"],"award-info":[{"award-number":["61751201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2019,12]]},"DOI":"10.1007\/s00521-019-04430-3","type":"journal-article","created":{"date-parts":[[2019,8,29]],"date-time":"2019-08-29T14:03:31Z","timestamp":1567087411000},"page":"9113-9126","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["An input information enhanced model for relation extraction"],"prefix":"10.1007","volume":"31","author":[{"given":"Ming","family":"Lei","sequence":"first","affiliation":[]},{"given":"Heyan","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Chong","family":"Feng","sequence":"additional","affiliation":[]},{"given":"Yang","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Chao","family":"Su","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,29]]},"reference":[{"key":"4430_CR1","unstructured":"Zhang X, Zhao J, LeCun Y, (2015) Character-level convolutional networks for text classification. In: Proceedings of the 28th international conference on neural information processing systems - volume 1, NIPS\u201915, pp 649\u2013657"},{"key":"4430_CR2","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1162\/tacl_a_00104","volume":"4","author":"J Chiu","year":"2016","unstructured":"Chiu J, Nichols E (2016) Named entity recognition with bidirectional LSTM-CNNs. Trans Assoc Comput Linguist 4:357","journal-title":"Trans Assoc Comput Linguist"},{"key":"4430_CR3","doi-asserted-by":"publisher","unstructured":"Cao K, Rei M (2016) A joint model for word embedding and word morphology. In: Proceedings of the 1st workshop on representation learning for NLP (Association for Computational Linguistics, 2016), pp 18\u201326. \n                    https:\/\/doi.org\/10.18653\/v1\/W16-1603\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/W16-1603","DOI":"10.18653\/v1\/W16-1603"},{"key":"4430_CR4","doi-asserted-by":"publisher","unstructured":"Ma X, Hovy E (2016) End-to-end sequence labeling via bi-directional LSTM-CNNs-CRF. In: Proceedings of the 54th annual meeting of the association for computational linguistics (volume 1: long papers) (Association for Computational Linguistics, 2016), pp 1064\u20131074. \n                    https:\/\/doi.org\/10.18653\/v1\/P16-1101\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/P16-1101","DOI":"10.18653\/v1\/P16-1101"},{"key":"4430_CR5","doi-asserted-by":"publisher","unstructured":"Miwa M, Bansal M (2016) Modeling joint entity and relation extraction with table representation. In: Proceedings of the 54th annual meeting of the association for computational linguistics (volume 1: long papers) (Association for Computational Linguistics, 2016), pp 1105\u20131116. \n                    https:\/\/doi.org\/10.18653\/v1\/P16-1105\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/P16-1105","DOI":"10.18653\/v1\/P16-1105"},{"key":"4430_CR6","doi-asserted-by":"publisher","unstructured":"Zheng S, Wang F, Bao H, Hao Y, Zhou P, Xu B (2017) Joint extraction of entities and relations based on a novel tagging scheme. In: Proceedings of the 55th annual meeting of the association for computational linguistics (volume 1: long papers) (Association for Computational Linguistics, 2017), pp 1227\u20131236. \n                    https:\/\/doi.org\/10.18653\/v1\/P17-1113\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/P17-1113","DOI":"10.18653\/v1\/P17-1113"},{"issue":"8","key":"4430_CR7","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Backpropagation applied to handwritten zip code recognition. Neural Comput 9(8):1735. \n                    https:\/\/doi.org\/10.1162\/neco.1997.9.8.1735","journal-title":"Neural Comput"},{"key":"4430_CR8","unstructured":"Graves A, Jaitly N, Mohamed AR (2014) Hybrid speech recognition with deep bidirectional LSTM. Automatic speech recognition and understanding IEEE, pp 273\u2013278"},{"key":"4430_CR9","doi-asserted-by":"crossref","unstructured":"Hearst MA (1992) Automatic acquisition of hyponyms from large text corpora. In: COLING 1992 volume 2: the 15th international conference on computational linguistics. \n                    http:\/\/www.aclweb.org\/anthology\/C92-2082","DOI":"10.3115\/992133.992154"},{"key":"4430_CR10","doi-asserted-by":"crossref","unstructured":"Brin S (1999) Extracting patterns and relations from the World Wide Web. In: Selected papers from the international workshop on The World Wide Web and databases, WebDB \u201998. Springer, London. pp 172\u2013183. \n                    http:\/\/dl.acm.org\/citation.cfm?id=646543.696220","DOI":"10.1007\/10704656_11"},{"key":"4430_CR11","doi-asserted-by":"publisher","unstructured":"Agichtein E, Gravano L (2000) Snowball: extracting relations from large plain-text collections. In: Proceedings of the fifth ACM conference on digital libraries, DL \u201900. ACM, New York, pp 85\u201394. \n                    https:\/\/doi.org\/10.1145\/336597.336644","DOI":"10.1145\/336597.336644"},{"key":"4430_CR12","doi-asserted-by":"publisher","unstructured":"Blum A, Lafferty J, Rwebangira MR, Reddy R (2004) Semi-supervised learning using randomized mincuts. In: Proceedings of the twenty-first international conference on machine learning, ICML \u201904. ACM, New York, p 13. \n                    https:\/\/doi.org\/10.1145\/1015330.1015429","DOI":"10.1145\/1015330.1015429"},{"key":"4430_CR13","unstructured":"Oakes MP (2005) Using Hearst\u2019s rules for the automatic acquisition of hyponyms for mining a pharmaceutical corpus. In: International workshop text mining research, practice and opportunities, proceedings, Borovets, Bulgaria, 24 September 2005. Held in Conjunction with Ranlp 63\u201367"},{"key":"4430_CR14","doi-asserted-by":"crossref","unstructured":"Chen J, Ji D, Tan C.L, Niu Z (2006) Relation extraction using label propagation based semi-supervised learning. In: Proceedings of the 21st international conference on computational linguistics and 44th annual meeting of the association for computational linguistics (Association for Computational Linguistics, 2006), pp 129\u2013136. \n                    http:\/\/www.aclweb.org\/anthology\/P06-1017","DOI":"10.3115\/1220175.1220192"},{"key":"4430_CR15","unstructured":"Bunescu R, Mooney R (2007) Learning to extract relations from the Web using minimal supervision. In: Proceedings of the 45th annual meeting of the association of computational linguistics (Association for Computational Linguistics, 2007), pp 576\u2013583. \n                    http:\/\/www.aclweb.org\/anthology\/P07-1073"},{"key":"4430_CR16","doi-asserted-by":"publisher","unstructured":"Bollegala DT, Matsuo Y, Ishizuka M (2010) Relational duality: unsupervised extraction of semantic relations between entities on the Web. In: Proceedings of the 19th international conference on World Wide Web, WWW \u201910. ACM, New York, pp 151\u2013160. \n                    https:\/\/doi.org\/10.1145\/1772690.1772707","DOI":"10.1145\/1772690.1772707"},{"key":"4430_CR17","unstructured":"Nakashole N, Tylenda T, Weikum G (2013) Fine-grained semantic typing of emerging entities. In: Proceedings of the 51st annual meeting of the association for computational linguistics (volume 1: long papers) (Association for Computational Linguistics, 2013), pp 1488\u20131497. \n                    http:\/\/www.aclweb.org\/anthology\/P13-1146"},{"key":"4430_CR18","first-page":"1083","volume":"3","author":"D Zelenko","year":"2003","unstructured":"Zelenko D, Aone C, Richardella A (2003) Dropout: a simple way to prevent neural networks from overfitting. Mach Learn Res 3:1083","journal-title":"Mach Learn Res"},{"key":"4430_CR19","unstructured":"Bunescu RC, Mooney RJ (2005) Subsequence kernels for relation extraction. In: Proceedings of the 18th international conference on neural information processing systems, NIPS\u201905. MIT Press, Cambridge, pp 171\u2013178. \n                    http:\/\/dl.acm.org\/citation.cfm?id=2976248.2976270"},{"key":"4430_CR20","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 (Coling 2008) (Coling 2008 Organizing Committee, 2008), pp 697\u2013704. \n                    http:\/\/www.aclweb.org\/anthology\/C08-1088","DOI":"10.3115\/1599081.1599169"},{"key":"4430_CR21","doi-asserted-by":"publisher","unstructured":"Xu K, Feng Y, Huang S, Zhao D (2015) Semantic relation classification via convolutional neural networks with simple negative sampling. In: Proceedings of the 2015 conference on empirical methods in natural language processing (Association for Computational Linguistics, 2015), pp 536\u2013540. \n                    https:\/\/doi.org\/10.18653\/v1\/D15-1062\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/D15-1062","DOI":"10.18653\/v1\/D15-1062"},{"key":"4430_CR22","doi-asserted-by":"publisher","unstructured":"Zhang H, Sun Y, Zhao M, Chow TWS, Wu QMJ (2019) Understanding subtitles by character-level sequence-to-sequence learning. IEEE Trans Cybern. \n                    https:\/\/doi.org\/10.1109\/TCYB.2019.2900159","DOI":"10.1109\/TCYB.2019.2900159"},{"key":"4430_CR23","doi-asserted-by":"publisher","unstructured":"dos Santos C, Guimar\u00e3es V (2015) Boosting named entity recognition with neural character embeddings. In: Proceedings of the fifth named entity workshop (Association for Computational Linguistics, 2015), pp 25\u201333. \n                    https:\/\/doi.org\/10.18653\/v1\/W15-3904\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/W15-3904","DOI":"10.18653\/v1\/W15-3904"},{"issue":"2","key":"4430_CR24","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1109\/TII.2016.2601521","volume":"13","author":"H Zhang","year":"2017","unstructured":"Zhang H, Li J, Ji Y, Yue H (2017) Understanding subtitles by character-level sequence-to-sequence learning. IEEE Trans Ind Inform 13(2):616. \n                    https:\/\/doi.org\/10.1109\/TII.2016.2601521","journal-title":"IEEE Trans Ind Inform"},{"issue":"4","key":"4430_CR25","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1162\/neco.1989.1.4.541","volume":"1","author":"Y LeCun","year":"1989","unstructured":"LeCun Y, Boser B, Denker JS, Henderson D, Howard RE, Hubbard W, Jackel LD (1989) Long short-term memory. Neural Comput 1(4):541. \n                    https:\/\/doi.org\/10.1162\/neco.1989.1.4.541","journal-title":"Neural Comput"},{"key":"4430_CR26","doi-asserted-by":"publisher","unstructured":"Xu Y, Mou L, Li G, Chen Y, Peng H, Jin Z (2015) Classifying relations via long short term memory networks along shortest dependency paths. In: Proceedings of the 2015 conference on empirical methods in natural language processing (Association for Computational Linguistics, 2015), pp 1785\u20131794. \n                    https:\/\/doi.org\/10.18653\/v1\/D15-1206","DOI":"10.18653\/v1\/D15-1206"},{"key":"4430_CR27","unstructured":"Xu Y, Jia R, Mou L, Li G, Chen Y, Lu Y, Jin Z (2016) Improved relation classification by deep recurrent neural networks with data augmentation. In: Proceedings of COLING 2016, the 26th international conference on computational linguistics: technical papers (The COLING 2016 Organizing Committee, 2016), pp 1461\u20131470. \n                    http:\/\/www.aclweb.org\/anthology\/C16-1138"},{"key":"4430_CR28","unstructured":"Zhang S, Zheng D, Hu X, Yang M (2015) Bidirectional long short-term memory networks for relation classification. In: Proceedings of the 29th Pacific Asia conference on language, information and computation, pp 73\u201378. \n                    http:\/\/www.aclweb.org\/anthology\/Y15-1009"},{"key":"4430_CR29","unstructured":"Zeng D, Liu K, Lai S, Zhou G, Zhao J (2014) Relation classification via convolutional deep neural network. In: Proceedings of COLING 2014, the 25th international conference on computational linguistics: technical papers (Dublin City University and Association for Computational Linguistics, 2014), pp 2335\u20132344. \n                    http:\/\/www.aclweb.org\/anthology\/C14-1220"},{"key":"4430_CR30","doi-asserted-by":"publisher","unstructured":"Wang L, Cao Z, de\u00a0Melo G, Liu Z (2016) Relation classification via multi-level attention CNNs. In: Proceedings of the 54th annual meeting of the association for computational linguistics (volume 1: long papers) (Association for Computational Linguistics, 2016), pp 1298\u20131307. \n                    https:\/\/doi.org\/10.18653\/v1\/P16-1123\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/P16-1123","DOI":"10.18653\/v1\/P16-1123"},{"key":"4430_CR31","doi-asserted-by":"publisher","unstructured":"dos Santos C, Xiang B, Zhou B (2015) Classifying relations by ranking with convolutional neural networks. In: Proceedings of the 53rd annual meeting of the association for computational linguistics and the 7th international joint conference on natural language processing (volume 1: long papers) (Association for Computational Linguistics, 2015), pp 626\u2013634. \n                    https:\/\/doi.org\/10.3115\/v1\/P15-1061\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/P15-1061","DOI":"10.3115\/v1\/P15-1061"},{"key":"4430_CR32","doi-asserted-by":"publisher","unstructured":"Vu NT, Adel H, Gupta P, Sch\u00fctze H (2016) Combining recurrent and convolutional neural networks for relation classification. In: Proceedings of the 2016 conference of the North American chapter of the association for computational linguistics: human language technologies (Association for Computational Linguistics, 2016), pp 534\u2013539. \n                    https:\/\/doi.org\/10.18653\/v1\/N16-1065\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/N16-1065","DOI":"10.18653\/v1\/N16-1065"},{"key":"4430_CR33","unstructured":"Yang B, Cardie C (2013) Joint inference for fine-grained opinion extraction. In: Proceedings of the 51st annual meeting of the association for computational linguistics (volume 1: long papers) (Association for Computational Linguistics, 2013), pp 1640\u20131649. \n                    http:\/\/www.aclweb.org\/anthology\/P13-1161"},{"key":"4430_CR34","doi-asserted-by":"publisher","unstructured":"Singh S, Riedel S, Martin B, Zheng J, McCallum A (2013) Joint inference of entities, relations, and conference. In: Proceedings of the 2013 workshop on automated knowledge base construction, AKBC \u201913. ACM, New York, pp 1\u20136. \n                    https:\/\/doi.org\/10.1145\/2509558.2509559\n                    \n                  . \n                    http:\/\/doi.acm.org\/10.1145\/2509558.2509559","DOI":"10.1145\/2509558.2509559"},{"key":"4430_CR35","doi-asserted-by":"publisher","unstructured":"Miwa M, Sasaki Y (2014) Modeling joint entity and relation extraction with table representation. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP) (Association for Computational Linguistics, 2014), pp 1858\u20131869. \n                    https:\/\/doi.org\/10.3115\/v1\/D14-1200\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/D14-1200","DOI":"10.3115\/v1\/D14-1200"},{"key":"4430_CR36","doi-asserted-by":"publisher","unstructured":"Li Q, Ji H, 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) (Association for Computational Linguistics, 2014), pp. 402\u2013412. \n                    https:\/\/doi.org\/10.3115\/v1\/P14-1038\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/P14-1038","DOI":"10.3115\/v1\/P14-1038"},{"key":"4430_CR37","doi-asserted-by":"crossref","unstructured":"Mintz M, Bills S, Snow R, Jurafsky D (2009) Distant supervision for relation extraction without labeled data. In: Proceedings of the joint conference of the 47th annual meeting of the acl and the 4th international joint conference on natural language processing of the AFNLP (Association for Computational Linguistics, 2009), pp 1003\u20131011. \n                    http:\/\/www.aclweb.org\/anthology\/P09-1113","DOI":"10.3115\/1690219.1690287"},{"key":"4430_CR38","doi-asserted-by":"crossref","unstructured":"Riedel S, Yao L, Mccallum A (2010) Modeling relations and their mentions without labeled text. In: European conference on machine learning and knowledge discovery in databases, pp 148\u2013163","DOI":"10.1007\/978-3-642-15939-8_10"},{"key":"4430_CR39","unstructured":"Hoffmann R, Zhang C, Ling X, Zettlemoyer L, Weld DS (2011) Knowledge-based weak supervision for information extraction of overlapping relations. In: Proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies (Association for Computational Linguistics, 2011), pp 541\u2013550. \n                    http:\/\/www.aclweb.org\/anthology\/P11-1055"},{"key":"4430_CR40","doi-asserted-by":"publisher","unstructured":"Ren X, Wu Z, He W, Qu M, Voss C.R, Ji H, Abdelzaher TF, Han J (2017) CoType: joint extraction of typed entities and relations with knowledge bases. In: Proceedings of the 26th international conference on World Wide Web (International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 2017), WWW \u201917, pp 1015\u20131024. \n                    https:\/\/doi.org\/10.1145\/3038912.3052708\n                    \n                  . \n                    https:\/\/doi.org\/10.1145\/3038912.3052708","DOI":"10.1145\/3038912.3052708"},{"key":"4430_CR41","unstructured":"Mikolov T, Sutskever I, Chen K, Corrado G, Dean J (2013) Distributed representations of words and phrases and their compositionality. In: Proceedings of the 26th international conference on neural information processing systems - volume 2 (Curran Associates Inc., USA, 2013), NIPS\u201913, pp 3111\u20133119. \n                    http:\/\/dl.acm.org\/citation.cfm?id=2999792.2999959"},{"key":"4430_CR42","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1162\/tacl_a_00049","volume":"5","author":"N Peng","year":"2017","unstructured":"Peng N, Poon H, Quirk C, Toutanova K, Yih W (2017) Cross-sentence N-ary relation extraction with graph LSTMs. Trans Assoc Comput Linguist 5:101","journal-title":"Trans Assoc Comput Linguist"},{"key":"4430_CR43","doi-asserted-by":"publisher","unstructured":"Gormley MR, Yu M, Dredze M (2015) Improved relation extraction with feature-rich compositional embedding models. In: Proceedings of the 2015 conference on empirical methods in natural language processing (Association for Computational Linguistics, 2015), pp 1774\u20131784. \n                    https:\/\/doi.org\/10.18653\/v1\/D15-1205\n                    \n                  . \n                    http:\/\/www.aclweb.org\/anthology\/D15-1205","DOI":"10.18653\/v1\/D15-1205"},{"key":"4430_CR44","doi-asserted-by":"crossref","unstructured":"Tang J, Qu M, Wang M, Zhang M, Yan J, Mei Q (2015) LINE: large-scale information network embedding (WWW World Wide Web Consortium (W3C), 2015). \n                    https:\/\/www.microsoft.com\/en-us\/research\/publication\/line-large-scale-information-network-embedding\/","DOI":"10.1145\/2736277.2741093"},{"key":"4430_CR45","unstructured":"Socher R, Huval B, Manning CD, Ng AY (2012) Semantic compositionality through recursive matrix-vector spaces. In: Proceedings of the 2012 joint conference on empirical methods in natural language processing and computational natural language learning (Association for Computational Linguistics, 2012), pp 1201\u20131211. \n                    http:\/\/www.aclweb.org\/anthology\/D12-1110"},{"key":"4430_CR46","unstructured":"Kingma D.P, Ba J.L (2015) Adam: A Method for Stochastic Optimization. international conference on learning representations"},{"issue":"1","key":"4430_CR47","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava N, Hinton G, Krizhevsky A, Sutskever I, Salakhutdinov R (2014) Dropout: a simple way to prevent neural networks from overfitting. J Mach Learn Res 15(1):1929","journal-title":"J Mach Learn Res"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04430-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04430-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04430-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,27]],"date-time":"2020-08-27T23:51:01Z","timestamp":1598572261000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04430-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,29]]},"references-count":47,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2019,12]]}},"alternative-id":["4430"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04430-3","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2019,8,29]]},"assertion":[{"value":"7 March 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 August 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 August 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}