{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T16:15:37Z","timestamp":1779380137685,"version":"3.53.1"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,2,26]],"date-time":"2024-02-26T00:00:00Z","timestamp":1708905600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,2,26]],"date-time":"2024-02-26T00:00:00Z","timestamp":1708905600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U22A2032"],"award-info":[{"award-number":["U22A2032"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Statistical Science Research Project","award":["2022LY099"],"award-info":[{"award-number":["2022LY099"]}]},{"name":"Zhejiang Lab Open Research Project","award":["K2022KG0AB01"],"award-info":[{"award-number":["K2022KG0AB01"]}]},{"name":"Public Welfare Plan Research Project of Zhejiang Provincial Science and Technology Department","award":["LTGG23H260003"],"award-info":[{"award-number":["LTGG23H260003"]}]},{"name":"Zhejiang Statistical Science Research Project"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Vis"],"published-print":{"date-parts":[[2024,4]]},"DOI":"10.1007\/s12650-024-00955-5","type":"journal-article","created":{"date-parts":[[2024,2,26]],"date-time":"2024-02-26T15:02:43Z","timestamp":1708959763000},"page":"197-213","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Interactive optimization of relation extraction via knowledge graph representation learning"],"prefix":"10.1007","volume":"27","author":[{"given":"Yuhua","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuming","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rongdong","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenwei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuwei","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4783-6863","authenticated-orcid":false,"given":"Zhiguang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,2,26]]},"reference":[{"key":"955_CR1","unstructured":"Bordes A, Usunier N, Garcia-Duran A, Weston J, Yakhnenko O (2013) Translating embeddings for modeling multi-relational data. In:  Advances in neural information processing systems 26"},{"key":"955_CR2","doi-asserted-by":"crossref","unstructured":"Carlson A, Betteridge J, Kisiel B, Settles B, Hruschka E, Mitchell T (2010) Toward an architecture for never-ending language learning, vol 3","DOI":"10.1609\/aaai.v24i1.7519"},{"key":"955_CR3","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2020.3030443","author":"D Cashman","year":"2020","unstructured":"Cashman D, Xu S, Das S, Heimerl F, Liu C, Humayoun S, Gleicher M, Endert A, Chang R (2020) Cava: a visual analytics system for exploratory columnar data augmentation using knowledge graphs. IEEE Trans Vis Comput Gr. https:\/\/doi.org\/10.1109\/TVCG.2020.3030443","journal-title":"IEEE Trans Vis Comput Gr"},{"key":"955_CR4","doi-asserted-by":"publisher","first-page":"2636","DOI":"10.1109\/TVCG.2017.2758362","volume":"99","author":"W Chen","year":"2018","unstructured":"Chen W, Huang Z, Wu F, Zhu M, Maciejewski R (2018) VAUD: a visual analysis approach for exploring spatio-temporal urban data. IEEE Trans Vis Comput Gr 99:2636\u20132648","journal-title":"IEEE Trans Vis Comput Gr"},{"key":"955_CR5","unstructured":"Dang T, Franz N, Lud\u00e4scher B, Forbes A (2015) Provenancematrix: a visualization tool for multi-taxonomy alignments. In: CEUR workshop proceedings vol 1456, pp 13\u201324"},{"key":"955_CR6","doi-asserted-by":"crossref","unstructured":"Fionda V, Pirr\u00f2 G (2020) Learning triple embeddings from knowledge graphs. In: proceedings of the AAAI conference on artificial intelligence 34, pp 3874\u20133881","DOI":"10.1609\/aaai.v34i04.5800"},{"key":"955_CR7","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-020-0013-1","author":"D Han","year":"2022","unstructured":"Han D, Pan J, Rusheng P, Zhou D, Cao N, He J, Xu M, Chen W (2022) iNet: visual analysis of irregular transition in multivariate dynamic networks. Front Comput Sci. https:\/\/doi.org\/10.1007\/s11704-020-0013-1","journal-title":"Front Comput Sci"},{"key":"955_CR8","doi-asserted-by":"crossref","unstructured":"Hendrickx I, Kim S, Kozareva Z, Nakov P, Pad\u00f3 S, Pennacchiotti M, Romano L, Szpakowicz S (2010) Semeval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals, pp 33\u201338","DOI":"10.3115\/1621969.1621986"},{"key":"955_CR9","doi-asserted-by":"publisher","first-page":"1302","DOI":"10.1109\/TVCG.2007.70582","volume":"13","author":"N Henry Riche","year":"2007","unstructured":"Henry Riche N, Fekete J-D, McGuffin M (2007) Nodetrix: a hybrid visualization of social networks. IEEE Trans Vis Comput Gr 13:1302\u20139. https:\/\/doi.org\/10.1109\/TVCG.2007.70582","journal-title":"IEEE Trans Vis Comput Gr"},{"key":"955_CR10","doi-asserted-by":"publisher","unstructured":"Ji G, He S, Xu L, Liu K, Zhao J (2015) Knowledge graph embedding via dynamic mapping matrix, pp 687\u2013696. https:\/\/doi.org\/10.3115\/v1\/P15-1067","DOI":"10.3115\/v1\/P15-1067"},{"key":"955_CR11","doi-asserted-by":"crossref","unstructured":"Kalinowski A, An Y (2022) Repurposing knowledge graph embeddings for triple representation via weak supervision. In: 2022 international conference on intelligent data science technologies and applications (IDSTA), IEEE, pp 129\u2013137","DOI":"10.1109\/IDSTA55301.2022.9923036"},{"key":"955_CR12","doi-asserted-by":"publisher","unstructured":"Kratzwald B, Kunpeng G, Feuerriegel S, Diefenbach D (2020) Intkb: a verifiable interactive framework for knowledge base completion. https:\/\/doi.org\/10.18653\/v1\/2020.coling-main.490","DOI":"10.18653\/v1\/2020.coling-main.490"},{"key":"955_CR13","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2021.3114863","author":"H Li","year":"2021","unstructured":"Li H, Wang Y, Zhang S, Song Y, Qu H (2021) KG4Vis: a knowledge graph-based approach for visualization recommendation. IEEE Trans Vis Comput Gr. https:\/\/doi.org\/10.1109\/TVCG.2021.3114863","journal-title":"IEEE Trans Vis Comput Gr"},{"issue":"12","key":"955_CR14","doi-asserted-by":"publisher","first-page":"4980","DOI":"10.1109\/TVCG.2022.3184186","volume":"28","author":"Z Li","year":"2022","unstructured":"Li Z, Wang X, Yang W, Wu J, Zhang Z, Liu Z, Sun M, Zhang H, Liu S (2022) A unified understanding of deep nlp models for text classification. IEEE Trans Vis Comput Gr 28(12):4980\u20134994. https:\/\/doi.org\/10.1109\/TVCG.2022.3184186","journal-title":"IEEE Trans Vis Comput Gr"},{"key":"955_CR15","doi-asserted-by":"publisher","first-page":"2181","DOI":"10.1609\/aaai.v29i1.9491","volume":"29","author":"Y Lin","year":"2015","unstructured":"Lin Y, Liu Z, Sun M, Liu Y, Zhu X (2015) Learning entity and relation embeddings for knowledge graph completion. Proc AAAI 29:2181\u20132187. https:\/\/doi.org\/10.1609\/aaai.v29i1.9491","journal-title":"Proc AAAI"},{"key":"955_CR16","doi-asserted-by":"publisher","unstructured":"Liu S, Wang X, Chen J, Zhu J, Guo B (2015) Topicpanorama: a full picture of relevant topics. In: 2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014 - Proceedings 2014, pp 183\u2013192 https:\/\/doi.org\/10.1109\/VAST.2014.7042494","DOI":"10.1109\/VAST.2014.7042494"},{"issue":"1","key":"955_CR17","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1109\/TVCG.2016.2598831","volume":"23","author":"M Liu","year":"2017","unstructured":"Liu M, Shi J, Li Z, Li C, Zhu J, Liu S (2017) Towards better analysis of deep convolutional neural networks. IEEE Trans Vis Comput Gr 23(1):91\u2013100","journal-title":"IEEE Trans Vis Comput Gr"},{"key":"955_CR18","doi-asserted-by":"publisher","first-page":"1117","DOI":"10.1109\/TVCG.2021.3114687","volume":"28","author":"A-P Lohfink","year":"2021","unstructured":"Lohfink A-P, Duque Anton S, Leitte H, Garth C (2021) Knowledge rocks: adding knowledge assistance to visualization systems. IEEE Trans Vis Comput Gr 28:1117","journal-title":"IEEE Trans Vis Comput Gr"},{"key":"955_CR19","doi-asserted-by":"publisher","unstructured":"Ma C, Yang C, Yang F, Zhuang Y, Zhang Z, Jia H, Xie X (2018) Trajectory factory: tracklet cleaving and re-connection by deep siamese bi-gru for multiple object tracking. In: 2018 IEEE international conference on multimedia and Expo (ICME), pp 1\u20136. https:\/\/doi.org\/10.1109\/ICME.2018.8486454","DOI":"10.1109\/ICME.2018.8486454"},{"key":"955_CR20","doi-asserted-by":"publisher","unstructured":"Miwa M, Bansal M (2016) End-to-end relation extraction using lstms on sequences and tree structures, pp 1105\u20131116. https:\/\/doi.org\/10.18653\/v1\/P16-1105","DOI":"10.18653\/v1\/P16-1105"},{"key":"955_CR21","unstructured":"Nickel M, Tresp V, Kriegel H-P et al (2011) A three-way model for collective learning on multi-relational data. In: Icml 11, pp 3104482\u20133104584"},{"key":"955_CR22","doi-asserted-by":"publisher","unstructured":"Nickel M, Rosasco L, Poggio T (2015) Holographic embeddings of knowledge graphs. In: proceedings of the AAAI conference on artificial intelligence 30https:\/\/doi.org\/10.1609\/aaai.v30i1.10314","DOI":"10.1609\/aaai.v30i1.10314"},{"key":"955_CR23","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-021-0609-0","author":"Y Peng","year":"2023","unstructured":"Peng Y, Fan X, Chen R, Yu Z, Liu S, Chen Y, Ying Z, Zhou F (2023) Visual abstraction of dynamic network via improved multi-class blue noise sampling. Front Comput Sci. https:\/\/doi.org\/10.1007\/s11704-021-0609-0","journal-title":"Front Comput Sci"},{"key":"955_CR24","doi-asserted-by":"publisher","unstructured":"Schutz A, Buitelaar P (2005) Relext: a tool for relation extraction from text in ontology extension, pp 593\u2013606. https:\/\/doi.org\/10.1007\/11574620_43","DOI":"10.1007\/11574620_43"},{"key":"955_CR25","doi-asserted-by":"publisher","unstructured":"Sheng S, Zhou P, Wu X (2019) CEPV: a tree structure information extraction and visualization tool for big knowledge graph, pp 221\u2013228. https:\/\/doi.org\/10.1109\/ICBK.2019.00037","DOI":"10.1109\/ICBK.2019.00037"},{"key":"955_CR26","doi-asserted-by":"publisher","unstructured":"Shinyama Y, Sekine S (2006). Preemptive information extraction using unrestricted relation discovery. https:\/\/doi.org\/10.3115\/1220835.1220874","DOI":"10.3115\/1220835.1220874"},{"key":"955_CR27","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.2c00886","author":"G Sinclair","year":"2022","unstructured":"Sinclair G, Thillainadarajah I, Meyer B, Samano V, Sivasupramaniam S, Adams L, Willighagen E, Richard A, Walker M, Williams A (2022) Wikipedia on the comptox chemicals dashboard: connecting resources to enrich public chemical data. J Chem Inf Model. https:\/\/doi.org\/10.1021\/acs.jcim.2c00886","journal-title":"J Chem Inf Model"},{"key":"955_CR28","doi-asserted-by":"publisher","unstructured":"Sun K, Liu Y, Guo Z, Wang C (2016) EduVis: visualization for education knowledge graph based on web data, pp 138\u2013139. https:\/\/doi.org\/10.1145\/2968220.2968227","DOI":"10.1145\/2968220.2968227"},{"key":"955_CR29","unstructured":"Trouillon T, Welbl J, Riedel S, Gaussier \u00c9, Bouchard G (2016) Complex embeddings for simple link prediction. In: international conference on machine learning, PMLR, pp 2071\u20132080"},{"key":"955_CR30","doi-asserted-by":"publisher","unstructured":"Wang Z, Zhang J, Feng J, Chen Z (2014) Knowledge graph embedding by translating on hyperplanes. In: proceedings of the AAAI conference on artificial intelligence, 28.https:\/\/doi.org\/10.1609\/aaai.v28i1.8870","DOI":"10.1609\/aaai.v28i1.8870"},{"issue":"12","key":"955_CR31","doi-asserted-by":"publisher","first-page":"2724","DOI":"10.1109\/TKDE.2017.2754499","volume":"29","author":"Q Wang","year":"2017","unstructured":"Wang Q, Mao Z, Wang B, Guo L (2017) Knowledge graph embedding: a survey of approaches and applications. IEEE Trans Knowl Data Eng 29(12):2724\u20132743","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"6","key":"955_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11704-023-2691-y","volume":"17","author":"X Wang","year":"2023","unstructured":"Wang X, Wu Z, Huang W, Wei Y, Huang Z, Xu M, Chen W (2023) VIS+AI: integrating visualization with artificial intelligence for efficient data analysis. Front Comput Sci 17(6):1","journal-title":"Front Comput Sci"},{"key":"955_CR33","doi-asserted-by":"publisher","unstructured":"Weihua Y, Dong X (2021) Visual analysis of industrial knowledge graph research based on citespace, pp 297\u2013300. https:\/\/doi.org\/10.1109\/CMMNO53328.2021.9467534","DOI":"10.1109\/CMMNO53328.2021.9467534"},{"key":"955_CR34","doi-asserted-by":"publisher","unstructured":"Xi J, Ye L, Huang Q, Li X (2021) Tolerating data missing in breast cancer diagnosis from clinical ultrasound reports via knowledge graph inference, pp 3756\u20133764. https:\/\/doi.org\/10.1145\/3447548.3467106","DOI":"10.1145\/3447548.3467106"},{"issue":"4","key":"955_CR35","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1631\/FITEE.1900532","volume":"21","author":"J-z Xia","year":"2020","unstructured":"Xia J-z, Zhang Y-h, Ye H, Wang Y, Jiang G, Zhao Y, Xie C, Kui X-y, Liao S-h, Wang W-p (2020) Supoolvisor: a visual analytics system for mining pool surveillance. Front Inf Technol Electron Eng 21(4):507\u2013523. https:\/\/doi.org\/10.1631\/FITEE.1900532","journal-title":"Front Inf Technol Electron Eng"},{"issue":"1","key":"955_CR36","first-page":"734","volume":"29","author":"J Xia","year":"2022","unstructured":"Xia J, Huang L, Lin W, Zhao X, Wu J, Chen Y, Zhao Y, Chen W (2022) Interactive visual cluster analysis by contrastive dimensionality reduction. IEEE Trans Vis Comput Gr 29(1):734\u2013744","journal-title":"IEEE Trans Vis Comput Gr"},{"issue":"1","key":"955_CR37","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1109\/TVCG.2022.3209423","volume":"29","author":"J Xia","year":"2023","unstructured":"Xia J, Huang L, Lin W, Zhao X, Wu J, Chen Y, Zhao Y, Chen W (2023) Interactive visual cluster analysis by contrastive dimensionality reduction. IEEE Trans Vis Comput Gr 29(1):734\u2013744. https:\/\/doi.org\/10.1109\/TVCG.2022.3209423","journal-title":"IEEE Trans Vis Comput Gr"},{"key":"955_CR38","doi-asserted-by":"publisher","unstructured":"Xiao J, Zhou Z (2020) Chapter-level entity relationship extraction method based on joint learning, pp 75\u201378. https:\/\/doi.org\/10.1109\/IHMSC49165.2020.00025","DOI":"10.1109\/IHMSC49165.2020.00025"},{"key":"955_CR39","doi-asserted-by":"publisher","unstructured":"Xiong C, Power R, Callan J (2017) Explicit semantic ranking for academic search via knowledge graph embedding, pp 1271\u20131279. https:\/\/doi.org\/10.1145\/3038912.3052558","DOI":"10.1145\/3038912.3052558"},{"key":"955_CR40","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 https:\/\/doi.org\/10.18653\/v1\/D15-1062","DOI":"10.18653\/v1\/D15-1062"},{"key":"955_CR41","unstructured":"Yang B, Yih W-t, He X, Gao J, Deng L (2014) Embedding entities and relations for learning and inference in knowledge bases. arXiv preprint arXiv:1412.6575"},{"key":"955_CR42","unstructured":"Yang W, Liu M, Wang Z, Liu S (2024) Foundation models meet visualizations: challenges and opportunities. Computational Visual Media. arxiv: 2310.05771"},{"key":"955_CR43","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2209.15223d","author":"Z Ying","year":"2022","unstructured":"Ying Z, Luhao G, Huixuan X, Bai G, Zhang Z, Wei Q, Lin Y, Liu Y, Zhou F (2022) Astf: visual abstractions of time-varying patterns in radio signals. IEEE Trans Vis Comput Gr. https:\/\/doi.org\/10.48550\/arXiv.2209.15223d","journal-title":"IEEE Trans Vis Comput Gr"},{"key":"955_CR44","doi-asserted-by":"crossref","unstructured":"Yuyu Z, Dai H, Kozareva Z, Smola A, Song L (2017) Variational reasoning for question answering with knowledge graph. In: proceedings of the AAAI conference on artificial intelligence, 32","DOI":"10.1609\/aaai.v32i1.12057"},{"key":"955_CR45","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, pp 2335\u20132344"},{"key":"955_CR46","doi-asserted-by":"publisher","unstructured":"Zhang Y, Qi P, Manning C (2018) Graph convolution over pruned dependency trees improves relation extraction, pp 2205\u20132215. https:\/\/doi.org\/10.18653\/v1\/D18-1244","DOI":"10.18653\/v1\/D18-1244"},{"key":"955_CR47","doi-asserted-by":"crossref","unstructured":"Zhang N, Deng S, Sun Z, Wang G, Chen X, Zhang W, Chen H (2019) Long-tail relation extraction via knowledge graph embeddings and graph convolution networks","DOI":"10.18653\/v1\/N19-1306"},{"key":"955_CR48","doi-asserted-by":"crossref","unstructured":"Zhang Z, Cai J, Zhang Y, Wang J (2020) Learning hierarchy-aware knowledge graph embeddings for link prediction. In: proceedings of the AAAI conference on artificial intelligence 34, pp 3065\u20133072","DOI":"10.1609\/aaai.v34i03.5701"},{"key":"955_CR49","doi-asserted-by":"crossref","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","DOI":"10.18653\/v1\/P17-1113"},{"key":"955_CR50","doi-asserted-by":"publisher","unstructured":"Zhou P, Shi W, Tian J, Qi Z, Li B, Hao H, Xu B (2016) Attention-based bidirectional long short-term memory networks for relation classification, pp 207\u2013212. https:\/\/doi.org\/10.18653\/v1\/P16-2034","DOI":"10.18653\/v1\/P16-2034"},{"key":"955_CR51","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2020.3030440","author":"Z Zhou","year":"2020","unstructured":"Zhou Z, Shi C, Shen X, Cai L, Wang H, Liu Y, Ying Z, Chen W (2020a) Context-aware sampling of large networks via graph representation learning. IEEE Trans Vis Comput Gr. https:\/\/doi.org\/10.1109\/TVCG.2020.3030440","journal-title":"IEEE Trans Vis Comput Gr"},{"key":"955_CR52","doi-asserted-by":"publisher","unstructured":"Zhou Z, Zhang X, Yang Z, Chen Y, Liu Y, Wen J, Chen B, Ying Z, Chen W (2020b) Visual abstraction of geographical point data with spatial autocorrelations, pp 60\u201371. https:\/\/doi.org\/10.1109\/VAST50239.2020.00011","DOI":"10.1109\/VAST50239.2020.00011"},{"key":"955_CR53","doi-asserted-by":"publisher","DOI":"10.1109\/THMS.2022.3227181","author":"Z Zhou","year":"2022","unstructured":"Zhou Z, Sun L, Yu W, Liu Y, Xiang Z, Wang Y, Chen W (2022) iMGC: interactive multiple graph clustering with constrained Laplacian rank. IEEE Trans Hum Mach Syst. https:\/\/doi.org\/10.1109\/THMS.2022.3227181","journal-title":"IEEE Trans Hum Mach Syst"},{"key":"955_CR54","doi-asserted-by":"publisher","DOI":"10.1109\/THMS.2023.3296692","author":"Z Zhou","year":"2023","unstructured":"Zhou Z, Zheng F, Wen J, Chen Y, Li X, Liu Y, Wang Y, Chen W (2023) A user-driven sampling model for large-scale geographical point data visualization via convolutional neural networks. IEEE Trans Hum Mach Syst. https:\/\/doi.org\/10.1109\/THMS.2023.3296692","journal-title":"IEEE Trans Hum Mach Syst"}],"container-title":["Journal of Visualization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12650-024-00955-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12650-024-00955-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12650-024-00955-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T09:24:10Z","timestamp":1710840250000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12650-024-00955-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,26]]},"references-count":54,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,4]]}},"alternative-id":["955"],"URL":"https:\/\/doi.org\/10.1007\/s12650-024-00955-5","relation":{},"ISSN":["1343-8875","1875-8975"],"issn-type":[{"value":"1343-8875","type":"print"},{"value":"1875-8975","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,26]]},"assertion":[{"value":"4 November 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 December 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 February 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}