{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T14:34:03Z","timestamp":1762353243177,"version":"3.37.3"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,6,22]],"date-time":"2022-06-22T00:00:00Z","timestamp":1655856000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,6,22]],"date-time":"2022-06-22T00:00:00Z","timestamp":1655856000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100014103","name":"Key Technology Research and Development Program of Shandong","doi-asserted-by":"crossref","award":["2017YFC1703905"],"award-info":[{"award-number":["2017YFC1703905"]}],"id":[{"id":"10.13039\/100014103","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Sichuan Science and Technology Program","award":["2020YFS0372","2020YFS0302"],"award-info":[{"award-number":["2020YFS0372","2020YFS0302"]}]},{"name":"Sichuan Science and Technology Program","award":["2020YFS0283"],"award-info":[{"award-number":["2020YFS0283"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1007\/s11063-022-10906-6","type":"journal-article","created":{"date-parts":[[2022,6,22]],"date-time":"2022-06-22T14:03:09Z","timestamp":1655906589000},"page":"735-750","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Word-Concept Heterogeneous Graph Convolutional Network for Short Text Classification"],"prefix":"10.1007","volume":"55","author":[{"given":"Shigang","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4906-7025","authenticated-orcid":false,"given":"Yongguo","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiajing","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,22]]},"reference":[{"issue":"2","key":"10906_CR1","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1108\/IJWIS-12-2017-0083","volume":"15","author":"IM Alsmadi","year":"2019","unstructured":"Alsmadi IM, Gan KH (2019) Review of short-text classification. Int J Web Inf Syst 15(2):155\u2013182. https:\/\/doi.org\/10.1108\/IJWIS-12-2017-0083","journal-title":"Int J Web Inf Syst"},{"key":"10906_CR2","doi-asserted-by":"crossref","unstructured":"Arevian G (2007) Recurrent neural networks for robust real-world text classification. In: 2007 IEEE \/ WIC\/ACM international conference on web intelligence, WI 2007, 2\u20135 November 2007, Silicon Valley, CA, USA, Main Conference Proceedings, IEEE Computer Society, pp 326\u2013329. https:\/\/doi.org\/10.1109\/WI.2007.126","DOI":"10.1109\/WI.2007.126"},{"key":"10906_CR3","doi-asserted-by":"crossref","unstructured":"Batal I, Hauskrecht M (2009) Boosting KNN text classification accuracy by using supervised term weighting schemes. In: Cheung DW, Song I, Chu WW, Hu X, Lin JJ (eds) Proceedings of the 18th ACM conference on information and knowledge management, CIKM 2009, Hong Kong, China, November 2\u20136, 2009, ACM, pp 2041\u20132044. https:\/\/doi.org\/10.1145\/1645953.1646296","DOI":"10.1145\/1645953.1646296"},{"key":"10906_CR4","doi-asserted-by":"crossref","unstructured":"Chen J, Hu Y, Liu J, Xiao Y, Jiang H (2019) Deep short text classification with knowledge powered attention. In: The thirty-third aaai conference on artificial intelligence, AAAI 2019, the thirty-first innovative applications of artificial intelligence conference, IAAI 2019, The Ninth AAAI symposium on educational advances in artificial intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27\u2013February 1, 2019, AAAI Press, pp 6252\u20136259. https:\/\/doi.org\/10.1609\/aaai.v33i01.33016252","DOI":"10.1609\/aaai.v33i01.33016252"},{"issue":"4","key":"10906_CR5","doi-asserted-by":"publisher","first-page":"365","DOI":"10.7763\/IJMLC.2014.V4.438","volume":"4","author":"I Dilrukshi","year":"2014","unstructured":"Dilrukshi I, de Zoysa K (2014) A feature selection method for twitter news classification. Int J Mach Learn Comput 4(4):365","journal-title":"Int J Mach Learn Comput"},{"key":"10906_CR6","doi-asserted-by":"crossref","unstructured":"Ding W, Yu S, Wang Q, Yu J, Guo Q (2008) A novel naive bayesian text classifier. In: Yu F, Luo Q (eds) International symposium on information processing, ISIP 2008\/international pacific workshop on web mining, and web-based application, WMWA 2008, Moscow, Russia, 23\u201325 May 2008, IEEE Computer Society, pp 78\u201382.https:\/\/doi.org\/10.1109\/ISIP.2008.54","DOI":"10.1109\/ISIP.2008.54"},{"issue":"1","key":"10906_CR7","doi-asserted-by":"publisher","first-page":"50","DOI":"10.15837\/ijccc.2018.1.3142","volume":"13","author":"C Du","year":"2018","unstructured":"Du C, Huang L (2018) Text classification research with attention-based recurrent neural networks. Int J Comput Commun Control 13(1):50\u201361. https:\/\/doi.org\/10.15837\/ijccc.2018.1.3142","journal-title":"Int J Comput Commun Control"},{"key":"10906_CR8","doi-asserted-by":"crossref","unstructured":"Han E, Karypis G, Kumar V (2001) Text categorization using weight adjusted k-nearest neighbor classification. In: Cheung DW, Williams GJ, Li Q (eds) Knowledge discovery and data mining\u2014PAKDD 2001, 5th Pacific-Asia Conference, Hong Kong, China, April 16\u201318, 2001, Proceedings, Springer, Lecture Notes in Computer Science, vol 2035, pp 53\u201365.https:\/\/doi.org\/10.1007\/3-540-45357-1_9","DOI":"10.1007\/3-540-45357-1_9"},{"key":"10906_CR9","doi-asserted-by":"crossref","unstructured":"Hindi KME, Aljulaidan RR, AlSalman H (2020) Lazy fine-tuning algorithms for na\u00efve bayesian text classification. Appl Soft Comput 96:106652.https:\/\/doi.org\/10.1016\/j.asoc.2020.106652","DOI":"10.1016\/j.asoc.2020.106652"},{"key":"10906_CR10","doi-asserted-by":"crossref","unstructured":"Hu L, Yang T, Shi C, Ji H, Li X (2019) Heterogeneous graph attention networks for semi-supervised short text classification. In: Inui K, Jiang J, Ng V, Wan X (eds) Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3\u20137, 2019, Association for Computational Linguistics, pp 4820\u20134829.https:\/\/doi.org\/10.18653\/v1\/D19-1488","DOI":"10.18653\/v1\/D19-1488"},{"key":"10906_CR11","doi-asserted-by":"crossref","unstructured":"Huang L, Ma D, Li S, Zhang X, Wang H (2019) Text level graph neural network for text classification. In: Inui K, Jiang J, Ng V, Wan X (eds) Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3\u20137, 2019, Association for Computational Linguistics, pp 3442\u20133448.https:\/\/doi.org\/10.18653\/v1\/D19-1345","DOI":"10.18653\/v1\/D19-1345"},{"key":"10906_CR12","doi-asserted-by":"crossref","unstructured":"Islam MZ, Liu J, Li J, Liu L, Kang W (2019) A semantics aware random forest for text classification. In: Zhu W, Tao D, Cheng X, Cui P, Rundensteiner EA, Carmel D, He Q, Yu JX (eds) Proceedings of the 28th ACM international conference on information and knowledge management, CIKM 2019, Beijing, China, November 3\u20137, 2019, ACM, pp 1061\u20131070. https:\/\/doi.org\/10.1145\/3357384.3357891","DOI":"10.1145\/3357384.3357891"},{"key":"10906_CR13","doi-asserted-by":"crossref","unstructured":"Joulin A, Grave E, Bojanowski P, Mikolov T (2017) Bag of tricks for efficient text classification. In: Lapata M, Blunsom P, Koller A (eds) Proceedings of the 15th conference of the european chapter of the association for computational linguistics, EACL 2017, Valencia, Spain, April 3\u20137, 2017, Volume 2: Short Papers, Association for Computational Linguistics, pp 427\u2013431.https:\/\/doi.org\/10.18653\/v1\/e17-2068","DOI":"10.18653\/v1\/E17-2068"},{"key":"10906_CR14","doi-asserted-by":"crossref","unstructured":"Keerthi SS (2005) Generalized LARS as an effective feature selection tool for text classification with svms. In: Raedt LD, Wrobel S (eds) Machine learning, proceedings of the twenty-second international conference (ICML 2005), Bonn, Germany, August 7\u201311, 2005, ACM, ACM International Conference Proceeding Series, vol 119, pp 417\u2013424.https:\/\/doi.org\/10.1145\/1102351.1102404","DOI":"10.1145\/1102351.1102404"},{"key":"10906_CR15","doi-asserted-by":"crossref","unstructured":"Kim Y (2014) Convolutional neural networks for sentence classification. In: Moschitti A, Pang B, Daelemans W (eds) Proceedings of the 2014 conference on empirical methods in natural language processing, EMNLP 2014, October 25\u201329, 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL, ACL, pp 1746\u20131751.https:\/\/doi.org\/10.3115\/v1\/d14-1181","DOI":"10.3115\/v1\/D14-1181"},{"key":"10906_CR16","unstructured":"Kingma DP, Ba J (2015) Adam: a method for stochastic optimization. In: Bengio Y, LeCun Y (eds) 3rd international conference on learning representations, ICLR 2015, San Diego, CA, USA, May 7\u20139, 2015, Conference Track Proceedings.http:\/\/arxiv.org\/abs\/1412.6980"},{"key":"10906_CR17","doi-asserted-by":"crossref","unstructured":"Li C, Ouyang J, Li X (2019) Classifying extremely short texts by exploiting semantic centroids in word mover\u2019s distance space. In: Liu L, White RW, Mantrach A, Silvestri F, McAuley JJ, Baeza-Yates R, Zia L (eds) The world wide web conference, WWW 2019, San Francisco, CA, USA, May 13\u201317, 2019, ACM, pp 939\u2013949.https:\/\/doi.org\/10.1145\/3308558.3313397","DOI":"10.1145\/3308558.3313397"},{"issue":"2","key":"10906_CR18","doi-asserted-by":"publisher","first-page":"241","DOI":"10.34028\/iajit\/17\/2\/12","volume":"17","author":"Y Li","year":"2020","unstructured":"Li Y, Liu B (2020) A new vector representation of short texts for classification. Int Arab J Inf Technol 17(2):241\u2013249. https:\/\/doi.org\/10.34028\/iajit\/17\/2\/12","journal-title":"Int Arab J Inf Technol"},{"key":"10906_CR19","unstructured":"Li Y, Tarlow D, Brockschmidt M, Zemel RS (2016) Gated graph sequence neural networks. In: Bengio Y, LeCun Y (eds) 4th international conference on learning representations, ICLR 2016, San Juan, Puerto Rico, May 2\u20134, 2016, Conference Track Proceedings.http:\/\/arxiv.org\/abs\/1511.05493"},{"key":"#cr-split#-10906_CR20.1","unstructured":"Liu P, Qiu X, Huang X (2016) Recurrent neural network for text classification with multi-task learning. In: Kambhampati S"},{"key":"#cr-split#-10906_CR20.2","unstructured":"(ed) Proceedings of the twenty-fifth international joint conference on artificial intelligence, IJCAI 2016, New York, NY, USA, 9-15 July 2016, IJCAI\/AAAI Press, pp 2873-2879.http:\/\/www.ijcai.org\/Abstract\/16\/408"},{"key":"10906_CR21","doi-asserted-by":"crossref","unstructured":"Liu X, You X, Zhang X, Wu J, Lv P (2020) Tensor graph convolutional networks for text classification. In: The thirty-fourth AAAI conference on artificial intelligence, AAAI 2020, the thirty-second innovative applications of artificial intelligence conference, IAAI 2020, the tenth AAAI symposium on educational advances in artificial intelligence, EAAI 2020, New York, NY, USA, February 7\u201312, 2020, AAAI Press, pp 8409\u20138416.https:\/\/aaai.org\/ojs\/index.php\/AAAI\/article\/view\/6359","DOI":"10.1609\/aaai.v34i05.6359"},{"key":"10906_CR22","doi-asserted-by":"crossref","unstructured":"Niu G, Xu H, He B, Xiao X, Wu H, Gao S (2019) Enhancing local feature extraction with global representation for neural text classification. In: Inui K, Jiang J, Ng V, Wan X (eds) Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3\u20137, 2019, Association for Computational Linguistics, pp 496\u2013506.https:\/\/doi.org\/10.18653\/v1\/D19-1047","DOI":"10.18653\/v1\/D19-1047"},{"key":"10906_CR23","doi-asserted-by":"crossref","unstructured":"Pennington J, Socher R, Manning CD (2014) Glove: Global vectors for word representation. In: Moschitti A, Pang B, Daelemans W (eds) Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014, October 25-29, 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL, ACL, pp 1532\u20131543.https:\/\/doi.org\/10.3115\/v1\/d14-1162","DOI":"10.3115\/v1\/D14-1162"},{"key":"10906_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.is.2018.05.006","volume":"77","author":"T Salles","year":"2018","unstructured":"Salles T, Gon\u00e7alves MA, Rodrigues V, da Rocha LC (2018) Improving random forests by neighborhood projection for effective text classification. Inf Syst 77:1\u201321","journal-title":"Inf Syst"},{"issue":"1","key":"10906_CR25","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1109\/TNN.2008.2005605","volume":"20","author":"F Scarselli","year":"2009","unstructured":"Scarselli F, Gori M, Tsoi AC, Hagenbuchner M, Monfardini G (2009) The graph neural network model. IEEE Trans Neural Netw 20(1):61\u201380. https:\/\/doi.org\/10.1109\/TNN.2008.2005605","journal-title":"IEEE Trans Neural Netw"},{"key":"10906_CR26","doi-asserted-by":"crossref","unstructured":"Shanahan JG, Roma N (2003) Improving SVM text classification performance through threshold adjustment. In: Lavrac N, Gamberger D, Todorovski L, Blockeel H (eds) Machine learning: ECML 2003, 14th European conference on machine learning, Cavtat-Dubrovnik, Croatia, September 22\u201326, 2003, Proceedings, Springer, Lecture Notes in Computer Science, vol 2837, pp 361\u2013372.https:\/\/doi.org\/10.1007\/978-3-540-39857-8_33","DOI":"10.1007\/978-3-540-39857-8_33"},{"issue":"5","key":"10906_CR27","doi-asserted-by":"publisher","first-page":"635","DOI":"10.4304\/jmm.9.5.635-643","volume":"9","author":"G Song","year":"2014","unstructured":"Song G, Ye Y, Du X, Huang X, Bie S (2014) Short text classification: a survey. J Multim 9(5):635\u2013643. https:\/\/doi.org\/10.4304\/jmm.9.5.635-643","journal-title":"J Multim"},{"key":"10906_CR28","doi-asserted-by":"crossref","unstructured":"Tang J, Qu M, Mei Q (2015) PTE: predictive text embedding through large-scale heterogeneous text networks. In: Cao L, Zhang C, Joachims T, Webb GI, Margineantu DD, Williams G (eds) Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining, Sydney, NSW, Australia, August 10\u201313, 2015, ACM, pp 1165\u20131174.https:\/\/doi.org\/10.1145\/2783258.2783307","DOI":"10.1145\/2783258.2783307"},{"key":"10906_CR29","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017) Attention is all you need. In: Guyon I, von Luxburg U, Bengio S, Wallach HM, Fergus R, Vishwanathan SVN, Garnett R (eds) Advances in neural information processing systems 30: annual conference on neural information processing systems 2017, December 4\u20139, 2017, Long Beach, CA, USA, pp 5998\u20136008.http:\/\/papers.nips.cc\/paper\/7181-attention-is-all-you-need"},{"issue":"7","key":"10906_CR30","doi-asserted-by":"publisher","first-page":"8696","DOI":"10.1016\/j.eswa.2011.01.077","volume":"38","author":"S Wang","year":"2011","unstructured":"Wang S, Li D, Song X, Wei Y, Li H (2011) A feature selection method based on improved fisher\u2019s discriminant ratio for text sentiment classification. Expert Syst Appl 38(7):8696\u20138702. https:\/\/doi.org\/10.1016\/j.eswa.2011.01.077","journal-title":"Expert Syst Appl"},{"key":"10906_CR31","doi-asserted-by":"crossref","unstructured":"Xu B, Huang JZ, Williams GJ, Li MJ, Ye Y (2012) Hybrid random forests: advantages of mixed trees in classifying text data. In: Tan P, Chawla S, Ho CK, Bailey J (eds) Advances in knowledge discovery and data mining\u201416th Pacific-Asia conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29-June 1, 2012, Proceedings, Part I, Springer, Lecture Notes in Computer Science, vol 7301, pp 147\u2013158.https:\/\/doi.org\/10.1007\/978-3-642-30217-6_13","DOI":"10.1007\/978-3-642-30217-6_13"},{"key":"10906_CR32","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.neucom.2019.08.080","volume":"386","author":"J Xu","year":"2020","unstructured":"Xu J, Cai Y, Wu X, Lei X, Huang Q, Leung H, Li Q (2020) Incorporating context-relevant concepts into convolutional neural networks for short text classification. Neurocomputing 386:42\u201353. https:\/\/doi.org\/10.1016\/j.neucom.2019.08.080","journal-title":"Neurocomputing"},{"issue":"1","key":"10906_CR33","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1177\/0165551516677946","volume":"44","author":"S Xu","year":"2018","unstructured":"Xu S (2018) Bayesian na\u00efve bayes classifiers to text classification. J Inf Sci 44(1):48\u201359. https:\/\/doi.org\/10.1177\/0165551516677946","journal-title":"J Inf Sci"},{"key":"#cr-split#-10906_CR34.1","doi-asserted-by":"crossref","unstructured":"Yang Y, Wang H, Zhu J, Wu Y, Jiang K, Guo W, Shi W (2020) Dataless short text classification based on biterm topic model and word embeddings. In: Bessiere C","DOI":"10.24963\/ijcai.2020\/549"},{"key":"#cr-split#-10906_CR34.2","doi-asserted-by":"crossref","unstructured":"(ed) Proceedings of the twenty-ninth international joint conference on artificial intelligence, IJCAI 2020, ijcai.org, pp 3969-3975.https:\/\/doi.org\/10.24963\/ijcai.2020\/549","DOI":"10.24963\/ijcai.2020\/549"},{"key":"10906_CR35","doi-asserted-by":"crossref","unstructured":"Yao L, Mao C, Luo Y (2019) Graph convolutional networks for text classification. In: The thirty-third AAAI conference on artificial intelligence, AAAI 2019, the thirty-first innovative applications of artificial intelligence conference, IAAI 2019, the Ninth AAAI symposium on educational advances in artificial intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27\u2014February 1, 2019, AAAI Press, pp 7370\u20137377.https:\/\/doi.org\/10.1609\/aaai.v33i01.33017370","DOI":"10.1609\/aaai.v33i01.33017370"},{"key":"10906_CR36","doi-asserted-by":"crossref","unstructured":"Zeng J, Li J, Song Y, Gao C, Lyu MR, King I (2018) Topic memory networks for short text classification. In: Riloff E, Chiang D, Hockenmaier J, Tsujii J (eds) Proceedings of the 2018 conference on empirical methods in natural language processing, Brussels, Belgium, October 31\u2014November 4, 2018, Association for Computational Linguistics, pp 3120\u20133131.https:\/\/doi.org\/10.18653\/v1\/d18-1351","DOI":"10.18653\/v1\/D18-1351"},{"key":"10906_CR37","doi-asserted-by":"crossref","unstructured":"Zhang H, Ni W, Zhao M, Lin Z (2019) Cluster-gated convolutional neural network for short text classification. In: Bansal M, Villavicencio A (eds) Proceedings of the 23rd Conference on Computational Natural Language Learning, CoNLL 2019, Hong Kong, China, November 3-4, 2019, Association for Computational Linguistics, pp 1002\u20131011.https:\/\/doi.org\/10.18653\/v1\/K19-1094","DOI":"10.18653\/v1\/K19-1094"},{"key":"10906_CR38","doi-asserted-by":"crossref","unstructured":"Zhang Y, Yu X, Cui Z, Wu S, Wen Z, Wang L (2020) Every document owns its structure: Inductive text classification via graph neural networks. In: Jurafsky D, Chai J, Schluter N, Tetreault JR (eds) Proceedings of the 58th annual meeting of the association for computational linguistics, ACL 2020, Online, July 5\u201310, 2020, Association for Computational Linguistics, pp 334\u2013339. https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.31","DOI":"10.18653\/v1\/2020.acl-main.31"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-022-10906-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11063-022-10906-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-022-10906-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,6]],"date-time":"2023-03-06T14:28:55Z","timestamp":1678112935000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11063-022-10906-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,22]]},"references-count":40,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["10906"],"URL":"https:\/\/doi.org\/10.1007\/s11063-022-10906-6","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"type":"print","value":"1370-4621"},{"type":"electronic","value":"1573-773X"}],"subject":[],"published":{"date-parts":[[2022,6,22]]},"assertion":[{"value":"27 May 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 June 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}