{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T08:39:27Z","timestamp":1777365567607,"version":"3.51.4"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72171122"],"award-info":[{"award-number":["72171122"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J. King Saud Univ. Comput. Inf. Sci."],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s44443-025-00185-1","type":"journal-article","created":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T10:26:19Z","timestamp":1755599179000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Enhancing the efficiency of patent classification: a multimodal classification approach for design patents"],"prefix":"10.1007","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-0955-5450","authenticated-orcid":false,"given":"Xiaodong","family":"Xie","sequence":"first","affiliation":[]},{"given":"Jie","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Mengjia","family":"Xiang","sequence":"additional","affiliation":[]},{"given":"Jianting","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Yongxiang","family":"Sheng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,19]]},"reference":[{"key":"185_CR1","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.wpi.2018.07.002","volume":"55","author":"L Aristodemou","year":"2018","unstructured":"Aristodemou L, Tietze F (2018) The state-of-the-art on Intellectual Property Analytics (IPA): A literature review on artificial intelligence, machine learning and deep learning methods for analysing intellectual property (IP) data. World Pat Inf 55:37\u201351","journal-title":"World Pat Inf"},{"key":"185_CR2","doi-asserted-by":"crossref","unstructured":"Awale S, M\u00fcller-Budack E, Ewerth R (2025) Patent figure classification using large vision-language models.\u00a0arXiv:2501.12751. Accessed 3 July 2025","DOI":"10.1007\/978-3-031-88711-6_2"},{"key":"185_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109419","volume":"139","author":"S Bakkali","year":"2023","unstructured":"Bakkali S, Ming Z, Coustaty M, Rusi\u00f1ol M, Terrades OR (2023) VLCDoC: Vision-language contrastive pre-training model for cross-modal document classification. Pattern Recogn 139:109419","journal-title":"Pattern Recogn"},{"key":"185_CR4","doi-asserted-by":"crossref","unstructured":"Bakkali S, Biswas S, Ming Z, Coustaty M, Rusi\u00f1ol M, Terrades OR, Llad\u00f3s J (2025) GlobalDoc: A Cross-Modal Vision-Language Framework for Real-World Document Image Retrieval and Classification. In: 2025 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, pp 1436\u20131446","DOI":"10.1109\/WACV61041.2025.00147"},{"key":"185_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2024.123536","volume":"206","author":"H Bekamiri","year":"2024","unstructured":"Bekamiri H, Hain DS, Jurowetzki R (2024) Patentsberta: A deep NLP based hybrid model for patent distance and classification using augmented SBERT. Technol Forecast Soc Change 206:123536","journal-title":"Technol Forecast Soc Change"},{"key":"185_CR6","doi-asserted-by":"crossref","unstructured":"Cai J, Wang X, Guan C, Tang Y, Xu J, Zhong B, Zhu W (2022) Multimodal continual graph learning with neural architecture search. In: Proceedings of the ACM Web Conference 2022. ACM, pp 1292\u20131300","DOI":"10.1145\/3485447.3512176"},{"issue":"4","key":"185_CR7","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1016\/S0926-5805(03)00004-9","volume":"12","author":"CH Caldas","year":"2003","unstructured":"Caldas CH, Soibelman L (2003) Automating hierarchical document classification for construction management information systems. Automat Constr 12(4):395\u2013406","journal-title":"Automat Constr"},{"issue":"6285","key":"185_CR8","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1126\/science.aad2686","volume":"352","author":"L Cohen","year":"2016","unstructured":"Cohen L, Gurun UG, Kominers SD (2016) The growing problem of patent trolling. Science 352(6285):521\u2013522","journal-title":"Science"},{"issue":"5","key":"185_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2024.102083","volume":"36","author":"L Cui","year":"2024","unstructured":"Cui L (2024) A label learning approach using competitive population optimization algorithm feature selection to improve multi-label classification algorithms. J King Saud Univ Comput Inf Sci 36(5):102083","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"185_CR10","doi-asserted-by":"crossref","unstructured":"D'hondt E, Verberne S, Koster C, et al (2013) Text representations for patent classification. Comput Linguist 39(3):755\u2013775","DOI":"10.1162\/COLI_a_00149"},{"issue":"13s","key":"185_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3586075","volume":"55","author":"R Das","year":"2023","unstructured":"Das R, Singh TD (2023) Multimodal sentiment analysis: a survey of methods, trends, and challenges. ACM Comput Surv 55(13s):1\u201338","journal-title":"ACM Comput Surv"},{"issue":"1","key":"185_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2024.101925","volume":"36","author":"O Dib","year":"2024","unstructured":"Dib O, Nan Z, Liu J (2024) Machine learning-based ransomware classification of Bitcoin transactions. J King Saud Univ Comput Inf Sci 36(1):101925","journal-title":"J King Saud Univ Comput Inf Sci"},{"issue":"4","key":"185_CR13","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1038\/s42256-023-00624-6","volume":"5","author":"Y Ektefaie","year":"2023","unstructured":"Ektefaie Y, Dasoulas G, Noori A et al (2023) Multimodal learning with graphs. Nat Mach Intell 5(4):340\u2013350","journal-title":"Nat Mach Intell"},{"key":"185_CR14","doi-asserted-by":"crossref","unstructured":"Fall CJ, T\u00f6rcsv\u00e1ri A, Benzineb K, et al (2003) Automated categorization in the international patent classification. In: ACM SIGIR Forum. ACM, pp 10\u201325","DOI":"10.1145\/945546.945547"},{"key":"185_CR15","doi-asserted-by":"publisher","first-page":"7517","DOI":"10.1109\/TMM.2022.3222965","volume":"25","author":"X Fang","year":"2022","unstructured":"Fang X, Liu D, Zhou P, Hu Y (2022) Multi-modal cross-domain alignment network for video moment retrieval. IEEE Trans Multimedia 25:7517\u20137532","journal-title":"IEEE Trans Multimedia"},{"key":"185_CR16","doi-asserted-by":"crossref","unstructured":"Fink TMA, Reeves M, Palma R, Farr RS (2017) Serendipity and strategy in rapid innovation. Nat Commun 8(1):2002","DOI":"10.1038\/s41467-017-02042-w"},{"issue":"1","key":"185_CR17","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1007\/s11192-021-04179-4","volume":"127","author":"A Haghighian Roudsari","year":"2022","unstructured":"Haghighian Roudsari A, Afshar J, Lee W, Lee S (2022) PatentNet: multi-label classification of patent documents using deep learning based language understanding. Scientometrics 127(1):207\u2013231","journal-title":"Scientometrics"},{"key":"185_CR18","doi-asserted-by":"publisher","first-page":"1163","DOI":"10.1109\/TEM.2022.3152216","volume":"71","author":"S Jiang","year":"2022","unstructured":"Jiang S, Hu J, Magee CL, Luo J (2022) Deep learning for technical document classification. IEEE Trans Eng Manag 71:1163\u20131179","journal-title":"IEEE Trans Eng Manag"},{"key":"185_CR19","doi-asserted-by":"crossref","unstructured":"Khattar D, Goud JS, Gupta M, Varma V (2019) Mvae: Multimodal variational autoencoder for fake news detection. In: The World Wide Web Conference. ACM, pp 2915\u20132921","DOI":"10.1145\/3308558.3313552"},{"key":"185_CR20","doi-asserted-by":"publisher","first-page":"1804","DOI":"10.1016\/j.eswa.2007.01.033","volume":"34","author":"YG Kim","year":"2008","unstructured":"Kim YG, Suh JH, Park SC (2008) Visualization of patent analysis for emerging technology. Expert Syst Appl 34:1804\u20131812","journal-title":"Expert Syst Appl"},{"key":"185_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.wpi.2020.101983","volume":"62","author":"JS Lee","year":"2020","unstructured":"Lee JS, Hsiang J (2020) Patent claim generation by fine-tuning OpenAI GPT-2. World Pat Inf 62:101983","journal-title":"World Pat Inf"},{"issue":"2","key":"185_CR22","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1007\/s11192-018-2905-5","volume":"117","author":"S Li","year":"2018","unstructured":"Li S, Hu J, Cui Y, Hu J (2018) DeepPatent: patent classification with convolutional neural networks and word embedding. Scientometrics 117(2):721\u2013744","journal-title":"Scientometrics"},{"key":"185_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.126427","volume":"550","author":"J Li","year":"2023","unstructured":"Li J, Wang X, Lv G, Zeng Z (2023a) GraphMFT: A graph network based multimodal fusion technique for emotion recognition in conversation. Neurocomputing 550:126427","journal-title":"Neurocomputing"},{"issue":"11","key":"185_CR24","doi-asserted-by":"publisher","first-page":"6225","DOI":"10.1109\/TKDE.2024.3389694","volume":"36","author":"J Li","year":"2024","unstructured":"Li J, Bin Y, Peng L, Yang Y, Li Y, Jin H, Huang Z (2024) Focusing on relevant responses for multi-modal rumor detection. IEEE Trans Knowl Data Eng 36(11):6225\u20136236","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"185_CR25","doi-asserted-by":"publisher","unstructured":"Li EP, Li TR, Luo HS, Chu JL, Duan LX, Lv FM (2025)\u00a0Adaptive multi-scale language reinforcement for multimodal named\u00a0entity recognition. Multimodal graph fusion for patent\u2013paper alignment. IEEE Trans Multimedia:\u00a01\u201312.\u00a0https:\/\/doi.org\/10.1109\/TMM.2025.3543105","DOI":"10.1109\/TMM.2025.3543105"},{"key":"185_CR26","unstructured":"Li LH, Yatskar M, Yin D, Hsieh CJ, Chang KW (2019) Visualbert: a simple and performant baseline for vision and language. arXiv:1908.03557.\u00a0Accessed 3 July 2025"},{"key":"185_CR27","doi-asserted-by":"crossref","unstructured":"Li Y, Quan R, Zhu L, Yang Y (2023b) Efficient multimodal fusion via interactive prompting. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. IEEE, pp 2604\u20132613","DOI":"10.1109\/CVPR52729.2023.00256"},{"issue":"9","key":"185_CR28","doi-asserted-by":"publisher","first-page":"15546","DOI":"10.1109\/TITS.2022.3141827","volume":"23","author":"C Liu","year":"2022","unstructured":"Liu C, Zhu C, Xia X, Zhao J, Long H (2022) FFEDN: Feature fusion encoder decoder network for crack detection. IEEE Trans Intell Transp Syst 23(9):15546\u201315557","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"185_CR29","doi-asserted-by":"crossref","unstructured":"Liu Y, Wu H, Huang Z, Wang H, Ma J, Liu Q, Chen E, Tao H, Rui K (2020) Technical phrase extraction for patent mining: A multi-level approach. In: 2020 IEEE International Conference on Data Mining (ICDM). IEEE, pp 1142\u20131147","DOI":"10.1109\/ICDM50108.2020.00139"},{"key":"185_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106873","volume":"218","author":"J Luo","year":"2021","unstructured":"Luo J, Sarica S, Wood KL (2021) Guiding data-driven design ideation by knowledge distance. Knowl Based Syst 218:106873","journal-title":"Knowl Based Syst"},{"key":"185_CR31","first-page":"116084","volume":"37","author":"D Madaan","year":"2024","unstructured":"Madaan D, Makino T, Chopra S, Cho K (2024) Jointly modeling inter- & intra-modality dependencies for multi-modal learning. Adv Neural Inf Process Syst 37:116084\u2013116105","journal-title":"Adv Neural Inf Process Syst"},{"issue":"2","key":"185_CR32","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1002\/smj.3441","volume":"44","author":"M Miric","year":"2023","unstructured":"Miric M, Jia N, Huang KG (2023) Using supervised machine learning for large-scale classification in management research: The case for identifying artificial intelligence patents. Strateg Manag J 44(2):491\u2013519","journal-title":"Strateg Manag J"},{"key":"185_CR33","doi-asserted-by":"publisher","first-page":"1142","DOI":"10.1609\/aaai.v39i12.33358","volume":"39","author":"Y Qi","year":"2025","unstructured":"Qi Y, Zhang Q, Lin X, Su X, Zhu J, Wang J, Li J (2025) Seeing beyond noise: Joint graph structure evaluation and denoising for multimodal recommendation. In Proceedings of the AAAI Conference on Artificial Intelligence 39:1142\u20131147","journal-title":"In Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"185_CR34","doi-asserted-by":"crossref","unstructured":"Qin Z, Zhang P, Wu F, Li X (2021) Fcanet: Frequency channel attention networks. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision. IEEE, pp 783\u2013792","DOI":"10.1109\/ICCV48922.2021.00082"},{"key":"185_CR35","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1007\/s10115-018-1322-7","volume":"61","author":"W Shalaby","year":"2019","unstructured":"Shalaby W, Zadrozny W (2019) Patent retrieval: a literature review. Knowl Inf Syst 61:631\u2013660","journal-title":"Knowl Inf Syst"},{"key":"185_CR36","first-page":"125520","volume":"37","author":"HH Shomee","year":"2024","unstructured":"Shomee HH, Wang Z, Ravi S, Medya S (2024) Impact: a large-scale integrated multimodal patent analysis and creation dataset for design patents. Adv Neural Inf Process Syst 37:125520\u2013125546","journal-title":"Adv Neural Inf Process Syst"},{"key":"185_CR37","doi-asserted-by":"crossref","unstructured":"Shul Y, Choi JW (2024) Cst-former: Transformer with channel-spectro-temporal attention for sound event localization and detection. In: ICASSP 2024 \u2013 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, pp 8686\u20138690","DOI":"10.1109\/ICASSP48485.2024.10447181"},{"key":"185_CR38","doi-asserted-by":"crossref","unstructured":"Tan H, Bansal M (2019) LXMERT: Learning cross-modality encoder representations from transformers. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). ACL, pp 5100\u20135111","DOI":"10.18653\/v1\/D19-1514"},{"key":"185_CR39","doi-asserted-by":"crossref","unstructured":"Thakur N, Reimers N, Daxenberger J, Gurevych I (2021) Augmented SBERT: Data augmentation method for improving bi-encoders for pairwise sentence scoring tasks. In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. ACL, pp 296\u2013310","DOI":"10.18653\/v1\/2021.naacl-main.28"},{"key":"185_CR40","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.neucom.2021.01.060","volume":"439","author":"Y Tian","year":"2021","unstructured":"Tian Y, Sun X, Yu H, Li Y, Fu K (2021) Hierarchical self-adaptation network for multimodal named entity recognition in social media. Neurocomputing 439:12\u201321","journal-title":"Neurocomputing"},{"issue":"4","key":"185_CR41","doi-asserted-by":"publisher","first-page":"755","DOI":"10.1016\/j.eswa.2006.01.013","volume":"31","author":"AJC Trappey","year":"2006","unstructured":"Trappey AJC, Hsu FC, Trappey CV, Lin CI (2006) Development of a patent document classification and search platform using a back-propagation network. Expert Syst Appl 31(4):755\u2013765","journal-title":"Expert Syst Appl"},{"issue":"5","key":"185_CR42","doi-asserted-by":"publisher","first-page":"1334","DOI":"10.1109\/TEM.2019.2957842","volume":"68","author":"AJ Trappey","year":"2019","unstructured":"Trappey AJ, Trappey CV, Govindarajan UH, Sun J (2019) Patent value analysis using deep learning models\u2014The case of IoT technology mining for the manufacturing industry. IEEE Trans Eng Manag 68(5):1334\u20131346","journal-title":"IEEE Trans Eng Manag"},{"issue":"5","key":"185_CR43","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1016\/j.ipm.2006.11.011","volume":"43","author":"YH Tseng","year":"2007","unstructured":"Tseng YH, Lin CJ, Lin YI (2007) Text mining techniques for patent analysis. Inf Process Manag 43(5):1216\u20131247","journal-title":"Inf Process Manag"},{"key":"185_CR44","first-page":"5998","volume":"30","author":"A Vaswani","year":"2017","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017) Attention is all you need. Adv Neural Inf Process Syst 30:5998\u20136008","journal-title":"Adv Neural Inf Process Syst"},{"issue":"5","key":"185_CR45","doi-asserted-by":"publisher","first-page":"5481","DOI":"10.1109\/TPAMI.2022.3211086","volume":"45","author":"Y Wang","year":"2022","unstructured":"Wang Y, Sun F, Huang W, He F, Tao D (2022) Channel exchanging networks for multimodal and multitask dense image prediction. IEEE Trans Pattern Anal Mach Intell 45(5):5481\u20135496","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"185_CR46","doi-asserted-by":"publisher","first-page":"1164","DOI":"10.1016\/j.asoc.2009.11.033","volume":"10","author":"CH Wu","year":"2010","unstructured":"Wu CH, Ken Y, Huang T (2010) Patent classification system using a new hybrid genetic algorithm support vector machine. Appl Soft Comput 10(4):1164\u20131177","journal-title":"Appl Soft Comput"},{"issue":"3","key":"185_CR47","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3712309","volume":"16","author":"H Wu","year":"2025","unstructured":"Wu H, Zhang L, Zhu H, Liu Q, Chen E, Xiong H (2025) Examination process modeling for intelligent patent management: A multi-aspect neural sequential approach. ACM Trans Manag Inf Syst 16(3):1\u201323","journal-title":"ACM Trans Manag Inf Syst"},{"key":"185_CR48","doi-asserted-by":"publisher","unstructured":"Wu PS, Li H, Hu LW, Ge JR, Zeng NY (2024) A local-global attention fusion framework with tensor decomposition for medical diagnosis. IEEE\/CAA J Autom Sinica 11(6):1536\u20131538.\u00a0https:\/\/doi.org\/10.1109\/JAS.2023.124167","DOI":"10.1109\/JAS.2023.124167"},{"key":"185_CR49","doi-asserted-by":"crossref","unstructured":"Wu W, Wang X, Luo H, Wang J, Yang Y, Ouyang W (2023) Bidirectional cross-modal knowledge exploration for video recognition with pre-trained vision-language models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. IEEE, pp 6620\u20136630","DOI":"10.1109\/CVPR52729.2023.00640"},{"key":"185_CR50","doi-asserted-by":"crossref","unstructured":"Wu Y, Zhan P, Zhang Y, Wang L, Xu Z (2021) Multimodal fusion with co-attention networks for fake news detection. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. ACL, pp 2560\u20132569","DOI":"10.18653\/v1\/2021.findings-acl.226"},{"issue":"10","key":"185_CR51","doi-asserted-by":"publisher","first-page":"12113","DOI":"10.1109\/TPAMI.2023.3275156","volume":"45","author":"P Xu","year":"2023","unstructured":"Xu P, Zhu X, Clifton DA (2023a) Multimodal learning with transformers: A survey. IEEE Trans Pattern Anal Mach Intell 45(10):12113\u201312132","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"3","key":"185_CR52","doi-asserted-by":"publisher","first-page":"3136","DOI":"10.1007\/s10489-022-03592-3","volume":"53","author":"S Xu","year":"2023","unstructured":"Xu S, Liu X, Ma K, Dong F, Riskhan B, Xiang S (2023b) Rumor detection on social media using hierarchically aggregated feature via graph neural networks. Appl Intell 53(3):3136\u20133149","journal-title":"Appl Intell"},{"issue":"1","key":"185_CR53","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2024.103935","volume":"62","author":"M Yin","year":"2025","unstructured":"Yin M, Chen W, Zhu D, Jiang J (2025) Enhancing video rumor detection through multimodal deep feature fusion with time-sync comments. Inf Process Manag 62(1):103935","journal-title":"Inf Process Manag"},{"issue":"2","key":"185_CR54","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1109\/JPROC.2024.3369017","volume":"112","author":"H Zhang","year":"2024","unstructured":"Zhang H, Wu B, Yuan X et al (2024) Trustworthy graph neural networks: Aspects, methods, and trends. Proc IEEE 112(2):97\u2013139","journal-title":"Proc IEEE"},{"issue":"9","key":"185_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3649447","volume":"56","author":"F Zhao","year":"2024","unstructured":"Zhao F, Zhang C, Geng B (2024) Deep multimodal data fusion. ACM Comput Surv 56(9):1\u201336","journal-title":"ACM Comput Surv"}],"container-title":["Journal of King Saud University Computer and Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44443-025-00185-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44443-025-00185-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44443-025-00185-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T12:42:19Z","timestamp":1758112939000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44443-025-00185-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,19]]},"references-count":55,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["185"],"URL":"https:\/\/doi.org\/10.1007\/s44443-025-00185-1","relation":{},"ISSN":["1319-1578","2213-1248"],"issn-type":[{"value":"1319-1578","type":"print"},{"value":"2213-1248","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,19]]},"assertion":[{"value":"7 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 2025","order":3,"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 known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interests"}}],"article-number":"183"}}