{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,13]],"date-time":"2025-04-13T04:03:08Z","timestamp":1744516988557,"version":"3.40.4"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2025,2,8]],"date-time":"2025-02-08T00:00:00Z","timestamp":1738972800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,8]],"date-time":"2025-02-08T00:00:00Z","timestamp":1738972800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100018237","name":"AOARD","doi-asserted-by":"crossref","award":["FA23862214039","FA23862214039","FA23862214039"],"award-info":[{"award-number":["FA23862214039","FA23862214039","FA23862214039"]}],"id":[{"id":"10.13039\/100018237","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1007\/s10115-025-02345-1","type":"journal-article","created":{"date-parts":[[2025,2,8]],"date-time":"2025-02-08T14:31:18Z","timestamp":1739025078000},"page":"4487-4521","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["K-Bloom: unleashing the power of pre-trained language models in extracting knowledge graph with predefined relations"],"prefix":"10.1007","volume":"67","author":[{"given":"Trung","family":"Vo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Son T.","family":"Luu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Le-Minh","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,8]]},"reference":[{"key":"2345_CR1","doi-asserted-by":"publisher","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K (2019) BERT: pre-training of deep bidirectional transformers for language understanding. In: Burstein J, Doran C, Solorio T (eds) Proceedings of the 2019 conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171\u20134186. Association for Computational Linguistics, Minneapolis, Minnesota. https:\/\/doi.org\/10.18653\/v1\/N19-1423. https:\/\/aclanthology.org\/N19-1423","DOI":"10.18653\/v1\/N19-1423"},{"key":"2345_CR2","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown T, Mann B, Ryder N, Subbiah M, Kaplan JD, Dhariwal P, Neelakantan A, Shyam P, Sastry G, Askell A et al (2020) Language models are few-shot learners. Adv Neural Inf Process Syst 33:1877\u20131901","journal-title":"Adv Neural Inf Process Syst"},{"issue":"1","key":"2345_CR3","first-page":"5485","volume":"21","author":"C Raffel","year":"2020","unstructured":"Raffel C, Shazeer N, Roberts A, Lee K, Narang S, Matena M, Zhou Y, Li W, Liu PJ (2020) Exploring the limits of transfer learning with a unified text-to-text transformer. J Mach Learn Res 21(1):5485\u20135551","journal-title":"J Mach Learn Res"},{"key":"2345_CR4","doi-asserted-by":"publisher","unstructured":"Petroni F, Rockt\u00e4schel T, Riedel S, Lewis P, Bakhtin A, Wu Y, Miller A (2019) Language models as knowledge bases? 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), pp 2463\u20132473. Association for Computational Linguistics, Hong Kong, China. https:\/\/doi.org\/10.18653\/v1\/D19-1250. https:\/\/aclanthology.org\/D19-1250","DOI":"10.18653\/v1\/D19-1250"},{"issue":"4","key":"2345_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3447772","volume":"54","author":"A Hogan","year":"2021","unstructured":"Hogan A, Blomqvist E, Cochez M, d\u2019Amato C, Melo GD, Gutierrez C, Kirrane S, Gayo JEL, Navigli R, Neumaier S et al (2021) Knowledge graphs. ACM Comput Surv (CSUR) 54(4):1\u201337","journal-title":"ACM Comput Surv (CSUR)"},{"key":"2345_CR6","doi-asserted-by":"crossref","unstructured":"Bollacker K, Evans C, Paritosh P, Sturge T, Taylor J (2008) Freebase: a collaboratively created graph database for structuring human knowledge. In: Proceedings of the 2008 ACM SIGMOD international conference on management of data, pp 1247\u20131250","DOI":"10.1145\/1376616.1376746"},{"issue":"11","key":"2345_CR7","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1145\/219717.219748","volume":"38","author":"GA Miller","year":"1995","unstructured":"Miller GA (1995) Wordnet: a lexical database for English. Commun ACM 38(11):39\u201341","journal-title":"Commun ACM"},{"issue":"3","key":"2345_CR8","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/j.websem.2008.06.001","volume":"6","author":"FM Suchanek","year":"2008","unstructured":"Suchanek FM, Kasneci G, Weikum G (2008) YAGO: a large ontology from Wikipedia and wordnet. J Web Semant 6(3):203\u2013217","journal-title":"J Web Semant"},{"key":"2345_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2023.101921","volume":"56","author":"J Deng","year":"2023","unstructured":"Deng J, Chen C, Huang X, Chen W, Cheng L (2023) Research on the construction of event logic knowledge graph of supply chain management. Adv Eng Inform 56:101921","journal-title":"Adv Eng Inform"},{"issue":"8","key":"2345_CR10","doi-asserted-by":"publisher","first-page":"3549","DOI":"10.1109\/TKDE.2020.3028705","volume":"34","author":"Q Guo","year":"2020","unstructured":"Guo Q, Zhuang F, Qin C, Zhu H, Xie X, Xiong H, He Q (2020) A survey on knowledge graph-based recommender systems. IEEE Trans Knowl Data Eng 34(8):3549\u20133568","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2345_CR11","doi-asserted-by":"crossref","unstructured":"Liu J, Liu A, Lu X, Welleck S, West P, Bras RL, Choi Y, Hajishirzi H (2021) Generated knowledge prompting for commonsense reasoning. arXiv preprint arXiv:2110.08387","DOI":"10.18653\/v1\/2022.acl-long.225"},{"key":"2345_CR12","doi-asserted-by":"crossref","unstructured":"Deng S, Wang C, Li Z, Zhang N, Dai Z, Chen H, Xiong F, Yan M, Chen Q, Chen M et al (2023) Construction and applications of billion-scale pre-trained multimodal business knowledge graph. In: 2023 IEEE 39th international conference on data engineering (ICDE). IEEE, pp 2988\u20133002","DOI":"10.1109\/ICDE55515.2023.00229"},{"key":"2345_CR13","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1016\/j.procs.2022.01.091","volume":"199","author":"X Mao","year":"2022","unstructured":"Mao X, Sun H, Zhu X, Li J (2022) Financial fraud detection using the related-party transaction knowledge graph. Procedia Comput Sci 199:733\u2013740","journal-title":"Procedia Comput Sci"},{"key":"2345_CR14","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1162\/tacl_a_00104","volume":"4","author":"JP Chiu","year":"2016","unstructured":"Chiu JP, Nichols E (2016) Named entity recognition with bidirectional LSTM-CNNs. Trans Assoc Comput Linguist 4:357\u2013370","journal-title":"Trans Assoc Comput Linguist"},{"key":"2345_CR15","doi-asserted-by":"crossref","unstructured":"Zhou G, Su J, Zhang J, Zhang M (2005) Exploring various knowledge in relation extraction. In: Proceedings of the 43rd annual meeting of the association for computational linguistics (acl\u201905), pp 427\u2013434","DOI":"10.3115\/1219840.1219893"},{"key":"2345_CR16","doi-asserted-by":"crossref","unstructured":"Huang X, Zhang J, Li D, Li P (2019) Knowledge graph embedding based question answering. In: Proceedings of the twelfth ACM international conference on web search and data mining, pp 105\u2013113","DOI":"10.1145\/3289600.3290956"},{"key":"2345_CR17","doi-asserted-by":"crossref","unstructured":"Yu L, Tian F, Kuang P, Zhou F (2024) Amplifying diversity and quality in commonsense knowledge graph completion (student abstract). In: Proceedings of the AAAI conference on artificial intelligence, vol 38, pp 23699\u201323700","DOI":"10.1609\/aaai.v38i21.30531"},{"key":"2345_CR18","unstructured":"Google: Introducing the Knowledge Graph: things, not strings. https:\/\/blog.google\/products\/search\/introducing-knowledge-graph-things-not\/. [Online] Accessed 16 May 2012 (2012)"},{"key":"2345_CR19","doi-asserted-by":"crossref","unstructured":"Wang H, Zhao M, Xie X, Li W, Guo M (2019) Knowledge graph convolutional networks for recommender systems. In: The world wide web conference, pp 3307\u20133313","DOI":"10.1145\/3308558.3313417"},{"issue":"1","key":"2345_CR20","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/s10618-022-00891-8","volume":"37","author":"W Jin","year":"2023","unstructured":"Jin W, Zhao B, Yu H, Tao X, Yin R, Liu G (2023) Improving embedded knowledge graph multi-hop question answering by introducing relational chain reasoning. Data Min Knowl Disc 37(1):255\u2013288","journal-title":"Data Min Knowl Disc"},{"key":"2345_CR21","doi-asserted-by":"publisher","unstructured":"Hao S, Tan B, Tang K, Ni B, Shao X, Zhang H, Xing E, Hu Z (2023) BertNet: Harvesting knowledge graphs with arbitrary relations from pretrained language models. In: Rogers A, Boyd-Graber J, Okazaki N (eds) Findings of the association for computational linguistics: ACL 2023. Association for Computational Linguistics, Toronto, Canada, pp 5000\u20135015. https:\/\/doi.org\/10.18653\/v1\/2023.findings-acl.309. https:\/\/aclanthology.org\/2023.findings-acl.309","DOI":"10.18653\/v1\/2023.findings-acl.309"},{"key":"2345_CR22","doi-asserted-by":"publisher","unstructured":"Ghazvininejad M, Levy O, Liu Y, Zettlemoyer L (2019) Mask-predict: Parallel decoding of conditional masked language models. 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). Association for Computational Linguistics, Hong Kong, China, pp 6112\u20136121. https:\/\/doi.org\/10.18653\/v1\/D19-1633. https:\/\/aclanthology.org\/D19-1633","DOI":"10.18653\/v1\/D19-1633"},{"issue":"2","key":"2345_CR23","doi-asserted-by":"publisher","first-page":"1250","DOI":"10.1109\/TII.2021.3073726","volume":"18","author":"M Yang","year":"2021","unstructured":"Yang M, Chen K, Sun S, Han Z, Kong L, Meng Q (2021) A pattern driven graph ranking approach to attribute extraction for knowledge graph. IEEE Trans Ind Inf 18(2):1250\u20131259","journal-title":"IEEE Trans Ind Inf"},{"key":"2345_CR24","doi-asserted-by":"publisher","first-page":"735","DOI":"10.1007\/s11280-019-00765-y","volume":"23","author":"H Yu","year":"2020","unstructured":"Yu H, Li H, Mao D, Cai Q (2020) A relationship extraction method for domain knowledge graph construction. World Wide Web 23:735\u2013753","journal-title":"World Wide Web"},{"key":"2345_CR25","doi-asserted-by":"crossref","unstructured":"Deng W, Guo P, Yang J (2019) Medical entity extraction and knowledge graph construction. In: 2019 16th international computer conference on wavelet active media technology and information processing. IEEE, pp 41\u201344","DOI":"10.1109\/ICCWAMTIP47768.2019.9067598"},{"key":"2345_CR26","first-page":"1962","volume":"7","author":"K Bollacker","year":"2007","unstructured":"Bollacker K, Cook R, Tufts P (2007) Freebase: a shared database of structured general human knowledge. AAAI 7:1962\u20131963","journal-title":"AAAI"},{"key":"2345_CR27","doi-asserted-by":"publisher","first-page":"678","DOI":"10.7551\/mitpress\/7287.001.0001","volume-title":"Wordnet: An electronic lexical database","author":"C Fellbaum","year":"1998","unstructured":"Fellbaum C (1998) Wordnet: An electronic lexical database, vol 2. MIT Press, Cambridge, pp 678\u2013686"},{"key":"2345_CR28","doi-asserted-by":"crossref","unstructured":"Vrande\u010di\u0107 D (2012) Wikidata: a new platform for collaborative data collection. In: Proceedings of the 21st international conference on world wide web, pp 1063\u20131064","DOI":"10.1145\/2187980.2188242"},{"key":"2345_CR29","doi-asserted-by":"crossref","unstructured":"Yates A, Banko M, Broadhead M, Cafarella MJ, Etzioni O, Soderland S (2007) Textrunner: open information extraction on the web. In: Proceedings of human language technologies: the annual conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT), pp 25\u201326","DOI":"10.3115\/1614164.1614177"},{"key":"2345_CR30","unstructured":"Fader A, Soderland S, Etzioni O (2011) Identifying relations for open information extraction. In: Proceedings of the 2011 conference on empirical methods in natural language processing, pp 1535\u20131545"},{"key":"2345_CR31","unstructured":"Schmitz M, Soderland S, Bart R, Etzioni O et al (2012) Open language learning for information extraction. In: Proceedings of the 2012 joint conference on empirical methods in natural language processing and computational natural language learning, pp 523\u2013534"},{"key":"2345_CR32","doi-asserted-by":"crossref","unstructured":"Suchanek FM, Kasneci G, Weikum G (2007) Yago: a core of semantic knowledge. In: Proceedings of the 16th international conference on world wide web, pp 697\u2013706","DOI":"10.1145\/1242572.1242667"},{"key":"2345_CR33","unstructured":"Alivanistos D, Santamar\u00eda SB, Cochez M, Kalo J-C, Krieken E, Thanapalasingam T (2022) Prompting as probing: using language models for knowledge base construction. arXiv preprint arXiv:2208.11057"},{"key":"2345_CR34","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1162\/tacl_a_00324","volume":"8","author":"Z Jiang","year":"2020","unstructured":"Jiang Z, Xu FF, Araki J, Neubig G (2020) How can we know what language models know? Trans Assoc Comput Linguist 8:423\u2013438","journal-title":"Trans Assoc Comput Linguist"},{"key":"2345_CR35","doi-asserted-by":"publisher","unstructured":"Poerner N, Waltinger U, Sch\u00fctze H (2020) E-BERT: efficient-yet-effective entity embeddings for BERT. In: Cohn T, He Y, Liu Y (eds) Findings of the association for computational linguistics: EMNLP 2020. Association for Computational Linguistics, pp 803\u2013818. https:\/\/doi.org\/10.18653\/v1\/2020.findings-emnlp.71. https:\/\/aclanthology.org\/2020.findings-emnlp.71","DOI":"10.18653\/v1\/2020.findings-emnlp.71"},{"key":"2345_CR36","doi-asserted-by":"publisher","unstructured":"Shin T, Razeghi Y, Logan IV RL, Wallace E, Singh S (2020) AutoPrompt: eliciting knowledge from language models with automatically generated prompts. In: Webber B, Cohn T, He Y, Liu Y (eds) Proceedings of the 2020 conference on empirical methods in natural language processing (EMNLP). Association for Computational Linguistics, pp 4222\u20134235. https:\/\/doi.org\/10.18653\/v1\/2020.emnlp-main.346. https:\/\/aclanthology.org\/2020.emnlp-main.346","DOI":"10.18653\/v1\/2020.emnlp-main.346"},{"key":"2345_CR37","unstructured":"Elazar Y, Kassner N, Ravfogel S, Feder A, Ravichander A, Mosbach M, Belinkov Y, Sch\u00fctze H, Goldberg Y (2022) Measuring causal effects of data statistics on language model\u2019s \u2018factual\u2019 predictions. arXiv preprint arXiv:2207.14251"},{"key":"2345_CR38","doi-asserted-by":"publisher","first-page":"1012","DOI":"10.1162\/tacl_a_00410","volume":"9","author":"Y Elazar","year":"2021","unstructured":"Elazar Y, Kassner N, Ravfogel S, Ravichander A, Hovy E, Sch\u00fctze H, Goldberg Y (2021) Measuring and improving consistency in pretrained language models. Trans Assoc Comput Linguist 9:1012\u20131031","journal-title":"Trans Assoc Comput Linguist"},{"key":"2345_CR39","doi-asserted-by":"publisher","unstructured":"Cao B, Lin H, Han X, Sun L, Yan L, Liao M, Xue T, Xu J (2021) Knowledgeable or educated guess? revisiting language models as knowledge bases. In: Zong C, Xia F, Li W, Navigli R (eds) Proceedings of the 59th annual meeting of the association for computational linguistics and the 11th international joint conference on natural language processing (volume 1: long papers). Association for Computational Linguistics, pp 1860\u20131874. https:\/\/doi.org\/10.18653\/v1\/2021.acl-long.146. https:\/\/aclanthology.org\/2021.acl-long.146","DOI":"10.18653\/v1\/2021.acl-long.146"},{"key":"2345_CR40","unstructured":"Kandpal N, Deng H, Roberts A, Wallace E, Raffel C (2023) Large language models struggle to learn long-tail knowledge. In: International conference on machine learning. PMLR, pp 15696\u201315707"},{"key":"2345_CR41","unstructured":"Grootendorst M. KeyBERT: Minimal Keyword Extraction with BERT. https:\/\/zenodo.org\/records\/4461265 Accessed 06 Dec 2023"},{"key":"2345_CR42","doi-asserted-by":"publisher","unstructured":"Arefyev N, Sheludko B, Podolskiy A, Panchenko A (2020) Always keep your target in mind: Studying semantics and improving performance of neural lexical substitution. In: Scott D, Bel N, Zong C (eds) Proceedings of the 28th international conference on computational linguistics. International Committee on Computational Linguistics, Barcelona, Spain, pp 1242\u20131255 (Online). https:\/\/doi.org\/10.18653\/v1\/2020.coling-main.107. https:\/\/aclanthology.org\/2020.coling-main.107","DOI":"10.18653\/v1\/2020.coling-main.107"},{"key":"2345_CR43","unstructured":"Zhang T, Kishore V, Wu F, Weinberger KQ, Artzi Y (2019) BERTScore: evaluating text generation with BERT. arXiv preprint arXiv:1904.09675"},{"key":"2345_CR44","doi-asserted-by":"crossref","unstructured":"Papineni K, Roukos S, Ward T, Zhu W-J (2002) BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th annual meeting of the association for computational linguistics, pp 311\u2013318","DOI":"10.3115\/1073083.1073135"},{"key":"2345_CR45","unstructured":"Kusner M, Sun Y, Kolkin N, Weinberger K (2015) From word embeddings to document distances. In: International conference on machine learning. PMLR, pp 957\u2013966"},{"key":"2345_CR46","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1023\/A:1026543900054","volume":"40","author":"Y Rubner","year":"2000","unstructured":"Rubner Y, Tomasi C, Guibas LJ (2000) The earth mover\u2019s distance as a metric for image retrieval. Int J Comput Vis 40:99\u2013121","journal-title":"Int J Comput Vis"},{"key":"2345_CR47","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.patrec.2023.04.012","volume":"170","author":"C Wei","year":"2023","unstructured":"Wei C, Wang B, Kuo C-CJ (2023) Synwmd: Syntax-aware word mover\u2019s distance for sentence similarity evaluation. Pattern Recogn Lett 170:48\u201355","journal-title":"Pattern Recogn Lett"},{"key":"2345_CR48","unstructured":"Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J (2013) Distributed representations of words and phrases and their compositionality. In: Advances in neural information processing systems, vol 26"},{"key":"2345_CR49","unstructured":"Radford A, Narasimhan K, Salimans T, Sutskever I, et al. (2018) Improving language understanding by generative pre-training"},{"issue":"10","key":"2345_CR50","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1145\/2629489","volume":"57","author":"D Vrande\u010di\u0107","year":"2014","unstructured":"Vrande\u010di\u0107 D, Kr\u00f6tzsch M (2014) Wikidata: a free collaborative knowledgebase. Commun ACM 57(10):78\u201385","journal-title":"Commun ACM"},{"key":"2345_CR51","unstructured":"Mendes P, Jakob M, Bizer C (2012) DBpedia: a multilingual cross-domain knowledge base. In: Calzolari N, Choukri K, Declerck T, Do\u011fan MU, Maegaard B, Mariani J, Moreno A, Odijk J, Piperidis S (eds) Proceedings of the eighth international conference on language resources and evaluation (LREC\u201912). European Language Resources Association (ELRA), Istanbul, Turkey, pp 1813\u20131817"},{"key":"2345_CR52","doi-asserted-by":"crossref","unstructured":"Vo D-T, Bagheri E (2017) Open information extraction. Encyclopedia with semantic computing and Robotic intelligence 1(01):1630003","DOI":"10.1142\/S2425038416300032"},{"key":"2345_CR53","unstructured":"Liu Y, Ott M, Goyal N, Du J, Joshi M, Chen D, Levy O, Lewis M, Zettlemoyer L, Stoyanov V (2019) Roberta: a robustly optimized bert pretraining approach. arXiv preprint arXiv:1907.11692"},{"key":"2345_CR54","doi-asserted-by":"crossref","unstructured":"Speer R, Chin J, Havasi C (2017) Conceptnet 5.5: an open multilingual graph of general knowledge. In: Proceedings of the AAAI conference on artificial intelligence, vol 31","DOI":"10.1609\/aaai.v31i1.11164"},{"key":"2345_CR55","first-page":"27263","volume":"34","author":"W Yuan","year":"2021","unstructured":"Yuan W, Neubig G, Liu P (2021) BARTScore: evaluating generated text as text generation. Adv Neural Inf Process Syst 34:27263\u201327277","journal-title":"Adv Neural Inf Process Syst"},{"key":"2345_CR56","unstructured":"Touvron H, Lavril T, Izacard G, Martinet X, Lachaux M-A, Lacroix T, Rozi\u00e8re B, Goyal N, Hambro E, Azhar F et al (2023) LLaMA: open and efficient foundation language models. arXiv preprint arXiv:2302.13971"},{"key":"2345_CR57","unstructured":"Jiang AQ, Sablayrolles A, Mensch A, Bamford C, Chaplot DS, Casas Ddl, Bressand F, Lengyel G, Lample G, Saulnier L et al (2023) Mistral 7b. arXiv preprint arXiv:2310.06825"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-025-02345-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-025-02345-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-025-02345-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,12]],"date-time":"2025-04-12T03:41:11Z","timestamp":1744429271000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-025-02345-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,8]]},"references-count":57,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,5]]}},"alternative-id":["2345"],"URL":"https:\/\/doi.org\/10.1007\/s10115-025-02345-1","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"type":"print","value":"0219-1377"},{"type":"electronic","value":"0219-3116"}],"subject":[],"published":{"date-parts":[[2025,2,8]]},"assertion":[{"value":"18 October 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 December 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 January 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 February 2025","order":4,"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 no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}