{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T15:07:56Z","timestamp":1764688076050,"version":"3.37.3"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"23","license":[{"start":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T00:00:00Z","timestamp":1704931200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T00:00:00Z","timestamp":1704931200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-18068-w","type":"journal-article","created":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T05:01:31Z","timestamp":1704949291000},"page":"63309-63328","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Feature Maps Correlation-based Video Quality Assessment"],"prefix":"10.1007","volume":"83","author":[{"given":"Amir Hossein","family":"Bakhtiari","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2556-6022","authenticated-orcid":false,"given":"Azadeh","family":"Mansouri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,11]]},"reference":[{"key":"18068_CR1","doi-asserted-by":"publisher","unstructured":"Dingquan LI, Tingting J, Jiang M (2019) Recent Advances and Challenges in Video Quality Assessment Special. https:\/\/doi.org\/10.12142\/ZTECOM.201901002","DOI":"10.12142\/ZTECOM.201901002"},{"key":"18068_CR2","unstructured":"\u201c10 YouTube Statistics That You Need to Know in 2022.\u201d https:\/\/www.oberlo.com\/blog\/youtube-statistics. Accessed Jul. 23, 2022"},{"key":"18068_CR3","doi-asserted-by":"publisher","first-page":"4449","DOI":"10.1109\/TIP.2021.3072221","volume":"30","author":"Z Tu","year":"2021","unstructured":"Tu Z, Wang Y, Birkbeck N, Adsumilli B, Bovik AC (2021) UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content. IEEE Trans Image Process 30:4449\u20134464. https:\/\/doi.org\/10.1109\/TIP.2021.3072221","journal-title":"IEEE Trans Image Process"},{"key":"18068_CR4","doi-asserted-by":"publisher","first-page":"14014","DOI":"10.1109\/CVPR46437.2021.01380","volume-title":"In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Z Ying","year":"2021","unstructured":"Ying Z, Mandal M, Ghadiyaram D, Bovik A (2021) Patch-VQ: \u2018Patching Up\u2019 the Video Quality Problem. In: In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp 14014\u201314024. https:\/\/doi.org\/10.1109\/CVPR46437.2021.01380"},{"key":"18068_CR5","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1109\/ICIP.2014.7025098","volume-title":"in 2014 IEEE International Conference on Image Processing (ICIP)","author":"J Xu","year":"2014","unstructured":"Xu J, Ye P, Liu Y, Doermann D (2014) No-reference video quality assessment via feature learning. In: in 2014 IEEE International Conference on Image Processing (ICIP). IEEE, pp 491\u2013495. https:\/\/doi.org\/10.1109\/ICIP.2014.7025098"},{"key":"18068_CR6","doi-asserted-by":"publisher","unstructured":"Ye P, Kumar J, Kang L, Doermann D (2012) Unsupervised feature learning framework for no-reference image quality assessment,\u201d in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. pp. 1098\u20131105. https:\/\/doi.org\/10.1109\/CVPR.2012.6247789","DOI":"10.1109\/CVPR.2012.6247789"},{"issue":"2","key":"18068_CR7","doi-asserted-by":"publisher","first-page":"684","DOI":"10.1109\/TIP.2013.2293423","volume":"23","author":"W Xue","year":"2014","unstructured":"Xue W, Zhang L, Mou X, Bovik AC (2014) Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index. IEEE Trans Image Proc 23(2):684\u2013695. https:\/\/doi.org\/10.1109\/TIP.2013.2293423","journal-title":"IEEE Trans Image Proc"},{"key":"18068_CR8","doi-asserted-by":"publisher","unstructured":"Seshadrinathan K, Bovik AC (2011) Temporal hysteresis model of time varying subjective video quality. In: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE. pp. 1153\u20131156. https:\/\/doi.org\/10.1109\/ICASSP.2011.5946613","DOI":"10.1109\/ICASSP.2011.5946613"},{"key":"18068_CR9","doi-asserted-by":"publisher","first-page":"2351","DOI":"10.1145\/3343031.3351028","volume-title":"Proceedings of the 27th ACM International Conference on Multimedia","author":"D Li","year":"2019","unstructured":"Li D, Jiang T, Jiang M (2019) Quality Assessment of In-the-Wild Videos. In: Proceedings of the 27th ACM International Conference on Multimedia. ACM, New York, NY, USA, pp 2351\u20132359. https:\/\/doi.org\/10.1145\/3343031.3351028"},{"issue":"12","key":"18068_CR10","doi-asserted-by":"publisher","first-page":"5923","DOI":"10.1109\/TIP.2019.2923051","volume":"28","author":"J Korhonen","year":"2019","unstructured":"Korhonen J (2019) Two-Level Approach for No-Reference Consumer Video Quality Assessment. IEEE Trans Image Proc 28(12):5923\u20135938. https:\/\/doi.org\/10.1109\/TIP.2019.2923051","journal-title":"IEEE Trans Image Proc"},{"key":"18068_CR11","doi-asserted-by":"publisher","first-page":"13430","DOI":"10.1109\/CVPR46437.2021.01323","volume-title":"In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Y Wang","year":"2021","unstructured":"Wang Y et al (2021) Rich features for perceptual quality assessment of UGC videos. In: In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp 13430\u201313439. https:\/\/doi.org\/10.1109\/CVPR46437.2021.01323"},{"key":"18068_CR12","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1145\/3394171.3413717","volume-title":"Proceedings of the 28th ACM International Conference on Multimedia","author":"P Chen","year":"2020","unstructured":"Chen P, Li L, Ma L, Wu J, Shi G (2020) RIRNet: Recurrent-In-Recurrent Network for Video Quality Assessment. In: Proceedings of the 28th ACM International Conference on Multimedia. ACM, New York, NY, USA, pp 834\u2013842. https:\/\/doi.org\/10.1145\/3394171.3413717"},{"issue":"2","key":"18068_CR13","doi-asserted-by":"publisher","first-page":"3081","DOI":"10.1007\/S11042-022-13383-0\/METRICS","volume":"82","author":"J Li","year":"2023","unstructured":"Li J, Li X (2023) Study on no-reference video quality assessment method incorporating dual deep learning networks. Multimed Tools Appl 82(2):3081\u20133100. https:\/\/doi.org\/10.1007\/S11042-022-13383-0\/METRICS","journal-title":"Multimed Tools Appl"},{"issue":"3","key":"18068_CR14","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","volume":"20","author":"A Mittal","year":"2013","unstructured":"Mittal A, Soundararajan R, Bovik AC (2013) Making a \u2018Completely Blind\u2019 Image Quality Analyzer. IEEE Signal Process Lett 20(3):209\u2013212. https:\/\/doi.org\/10.1109\/LSP.2012.2227726","journal-title":"IEEE Signal Process Lett"},{"issue":"3","key":"18068_CR15","doi-asserted-by":"publisher","first-page":"1352","DOI":"10.1109\/TIP.2014.2299154","volume":"23","author":"MA Saad","year":"2014","unstructured":"Saad MA, Bovik AC, Charrier C (2014) Blind Prediction of Natural Video Quality. IEEE Trans Image Process 23(3):1352\u20131365. https:\/\/doi.org\/10.1109\/TIP.2014.2299154","journal-title":"IEEE Trans Image Process"},{"key":"18068_CR16","doi-asserted-by":"publisher","first-page":"2400","DOI":"10.1109\/ICIP.2016.7532789","volume-title":"Proceedings - International Conference on Image Processing, ICIP","author":"K Manasa","year":"2016","unstructured":"Manasa K, Channappayya SS (2016) An optical flow-based no-reference video quality assessment algorithm. In: Proceedings - International Conference on Image Processing, ICIP. IEEE Computer Society, pp 2400\u20132404. https:\/\/doi.org\/10.1109\/ICIP.2016.7532789"},{"key":"18068_CR17","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1109\/OJSP.2021.3090333","volume":"2","author":"Z Tu","year":"2021","unstructured":"Tu Z, Yu X, Wang Y, Birkbeck N, Adsumilli B, Bovik AC (2021) RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content. IEEE Open J Signal Proc 2:425\u2013440. https:\/\/doi.org\/10.1109\/OJSP.2021.3090333","journal-title":"IEEE Open J Signal Proc"},{"key":"18068_CR18","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1109\/ICIP40778.2020.9191169","volume-title":"in 2020 IEEE International Conference on Image Processing (ICIP)","author":"Z Tu","year":"2020","unstructured":"Tu Z, Chen C-J, Chen L-H, Birkbeck N, Adsumilli B, Bovik AC (2020) A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment. In: in 2020 IEEE International Conference on Image Processing (ICIP). IEEE, pp 141\u2013145. https:\/\/doi.org\/10.1109\/ICIP40778.2020.9191169"},{"key":"18068_CR19","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1145\/3503161.3547849","volume-title":"Proceedings of the 30th ACM International Conference on Multimedia","author":"L Liao","year":"2022","unstructured":"Liao L et al (2022) Exploring the Effectiveness of Video Perceptual Representation in Blind Video Quality Assessment. In: Proceedings of the 30th ACM International Conference on Multimedia. ACM, New York, NY, USA, pp 837\u2013846. https:\/\/doi.org\/10.1145\/3503161.3547849"},{"issue":"3","key":"18068_CR20","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1109\/TBC.2022.3164332","volume":"68","author":"W Shen","year":"2022","unstructured":"Shen W et al (2022) An End-to-End No-Reference Video Quality Assessment Method With Hierarchical Spatiotemporal Feature Representation. IEEE Trans Broadcast 68(3):651\u2013660. https:\/\/doi.org\/10.1109\/TBC.2022.3164332","journal-title":"IEEE Trans Broadcast"},{"key":"18068_CR21","doi-asserted-by":"publisher","unstructured":"Guan X, Li F, Zhang Y, Cosman PC (2022) End-to-End Blind Video Quality Assessment Based on Visual and Memory Attention Modeling. IEEE Trans Multimed:1\u201316. https:\/\/doi.org\/10.1109\/TMM.2022.3189251","DOI":"10.1109\/TMM.2022.3189251"},{"key":"18068_CR22","doi-asserted-by":"publisher","first-page":"1302","DOI":"10.1109\/CVPRW59228.2023.00137","volume-title":"In: 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","author":"K Zhao","year":"2023","unstructured":"Zhao K, Yuan K, Sun M, Wen X (2023) Zoom-VQA: Patches, Frames and Clips Integration for Video Quality Assessment. In: In: 2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, pp 1302\u20131310. https:\/\/doi.org\/10.1109\/CVPRW59228.2023.00137"},{"key":"18068_CR23","doi-asserted-by":"publisher","first-page":"2414","DOI":"10.1109\/CVPR.2016.265","volume-title":"in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"LA Gatys","year":"2016","unstructured":"Gatys LA, Ecker AS, Bethge M (Jun. 2016) Image Style Transfer Using Convolutional Neural Networks. In: in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp 2414\u20132423. https:\/\/doi.org\/10.1109\/CVPR.2016.265"},{"issue":"3","key":"18068_CR24","doi-asserted-by":"publisher","first-page":"2595","DOI":"10.1007\/s11063-019-10036-6","volume":"50","author":"D Varga","year":"2019","unstructured":"Varga D (2019) No-Reference Video Quality Assessment Based on the Temporal Pooling of Deep Features. Neural Process Lett 50(3):2595\u20132608. https:\/\/doi.org\/10.1007\/s11063-019-10036-6","journal-title":"Neural Process Lett"},{"key":"18068_CR25","doi-asserted-by":"publisher","first-page":"5188","DOI":"10.1109\/CVPR.2015.7299155","volume-title":"In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"A Mahendran","year":"2015","unstructured":"Mahendran A, Vedaldi A (Jun. 2015) Understanding deep image representations by inverting them. In: In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp 5188\u20135196. https:\/\/doi.org\/10.1109\/CVPR.2015.7299155"},{"key":"18068_CR26","unstructured":"Simonyan K, Zisserman A, \u201cVery Deep Convolutional Networks for Large-Scale Image Recognition,\u201d Sep. 2014, [Online]. Available: http:\/\/arxiv.org\/abs\/1409.1556"},{"key":"18068_CR27","unstructured":"O. Russakovsky et al., \u201cImageNet Large Scale Visual Recognition Challenge,\u201d Sep. 2014, [Online]. Available: http:\/\/arxiv.org\/abs\/1409.0575"},{"key":"18068_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/ICME.2018.8486547","volume-title":"In: 2018 IEEE International Conference on Multimedia and Expo (ICME)","author":"Z Wang","year":"2018","unstructured":"Wang Z, Xiang X, Zhao Z, Su F (2018) Deep Image Retrieval: Indicator and Gram Matrix Weighting for Aggregated Convolutional Features. In: In: 2018 IEEE International Conference on Multimedia and Expo (ICME). IEEE, pp 1\u20136. https:\/\/doi.org\/10.1109\/ICME.2018.8486547"},{"issue":"4","key":"18068_CR29","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Trans Image Proc 13(4):600\u2013612. https:\/\/doi.org\/10.1109\/TIP.2003.819861","journal-title":"IEEE Trans Image Proc"},{"issue":"8","key":"18068_CR30","doi-asserted-by":"publisher","first-page":"1569","DOI":"10.1007\/s11760-019-01510-8","volume":"13","author":"D Varga","year":"2019","unstructured":"Varga D, Szir\u00e1nyi T (2019) No-reference video quality assessment via pretrained CNN and LSTM networks. Signal Image Video Proc 13(8):1569\u20131576. https:\/\/doi.org\/10.1007\/s11760-019-01510-8","journal-title":"Signal Image Video Proc"},{"key":"18068_CR31","doi-asserted-by":"publisher","DOI":"10.1109\/QOMEX.2019.8743252","volume-title":"In: 2019 11th International Conference on Quality of Multimedia Experience, QoMEX 2019","author":"H Lin","year":"2019","unstructured":"Lin H, Hosu V, Saupe D (2019) KADID-10k: A large-scale artificially distorted IQA database. In: In: 2019 11th International Conference on Quality of Multimedia Experience, QoMEX 2019. Institute of Electrical and Electronics Engineers Inc. https:\/\/doi.org\/10.1109\/QOMEX.2019.8743252"},{"key":"18068_CR32","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1016\/j.image.2018.12.016","volume":"74","author":"M Heydari","year":"2019","unstructured":"Heydari M, Cheraaqee P, Mansouri A, Mahmoudi-Aznaveh A (2019) A low complexity wavelet-based blind image quality evaluator. Signal Process Image Commun 74:280\u2013288. https:\/\/doi.org\/10.1016\/j.image.2018.12.016","journal-title":"Signal Process Image Commun"},{"key":"18068_CR33","doi-asserted-by":"crossref","unstructured":"Hosu V et al. (2017) The Konstanz Natural Video Database (KoNViD-1k). In: Ninth International Conference on Quality of Multimedia Experience (QoMEX)","DOI":"10.1109\/QoMEX.2017.7965673"},{"issue":"2","key":"18068_CR34","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1109\/TIP.2018.2869673","volume":"28","author":"Z Sinno","year":"2019","unstructured":"Sinno Z, Bovik AC (2019) Large-scale study of perceptual video quality. IEEE Trans Image Proc 28(2):612\u2013627. https:\/\/doi.org\/10.1109\/TIP.2018.2869673","journal-title":"IEEE Trans Image Proc"},{"key":"18068_CR35","unstructured":"Wang Y, Inguva S, Adsumilli B, \u201cYOUTUBE UGC DATASET FOR VIDEO COMPRESSION RESEARCH.\u201d [Online]. Available: https:\/\/media.withyoutube.com\/ugc-dataset"},{"key":"18068_CR36","doi-asserted-by":"publisher","unstructured":"K. Seshadrinathan, R. Soundararajan, A. C. Bovik, and L. K. Cormack, \u201cA subjective study to evaluate video quality assessment algorithms,\u201d in Human Vision and Electronic Imaging XV, SPIE, Feb. 2010, p. 75270H. https:\/\/doi.org\/10.1117\/12.845382.","DOI":"10.1117\/12.845382"},{"key":"18068_CR37","doi-asserted-by":"publisher","unstructured":"K. Seshadrinathan, R. Soundararajan, A. C. Bovik, and L. K. Cormack, \u201cStudy of subjective and objective quality assessment of video,\u201d IEEE Trans Image Proc, vol. 19, no. 6, pp. 1427\u20131441, Jun. 2010, https:\/\/doi.org\/10.1109\/TIP.2010.2042111","DOI":"10.1109\/TIP.2010.2042111"},{"key":"18068_CR38","doi-asserted-by":"publisher","first-page":"2818","DOI":"10.1109\/CVPR.2016.308","volume-title":"In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"C Szegedy","year":"2016","unstructured":"Szegedy C, Vanhoucke V, Ioffe S, Shlens J, Wojna Z (2016) Rethinking the Inception Architecture for Computer Vision. In: In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp 2818\u20132826. https:\/\/doi.org\/10.1109\/CVPR.2016.308"},{"key":"18068_CR39","unstructured":"Tan M, Le Qv (2019) EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. In: Proceedings of the 36th International Conference on Machine Learning. 97:6105-6114"},{"key":"18068_CR40","doi-asserted-by":"crossref","unstructured":"Bakhtiari AH, Mansouri A (2022) No-Reference Video Quality Assessment by Deep Feature Maps Relations. In: 12th International Conference on Computer and Knowledge Engineering (ICCKE 2022), November 17-18, 2022, Ferdowsi University of Mashhad, Iran","DOI":"10.1109\/ICCKE57176.2022.9960078"},{"key":"18068_CR41","doi-asserted-by":"publisher","first-page":"3311","DOI":"10.1145\/3394171.3413845","volume-title":"Proceedings of the 28th ACM International Conference on Multimedia","author":"J Korhonen","year":"2020","unstructured":"Korhonen J, Su Y, You J (2020) Blind Natural Video Quality Prediction via Statistical Temporal Features and Deep Spatial Features. In: Proceedings of the 28th ACM International Conference on Multimedia. ACM, New York, NY, USA, pp 3311\u20133319. https:\/\/doi.org\/10.1145\/3394171.3413845"},{"key":"18068_CR42","unstructured":"Wu H et al., \u201cDisCoVQA: Temporal Distortion-Content Transformers for Video Quality Assessment,\u201d Jun. 2022, [Online]. Available: http:\/\/arxiv.org\/abs\/2206.09853"},{"key":"18068_CR43","doi-asserted-by":"crossref","unstructured":"Wu H et al., \u201cFAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling,\u201d Jul. 2022, [Online]. Available: http:\/\/arxiv.org\/abs\/2207.02595","DOI":"10.1007\/978-3-031-20068-7_31"},{"issue":"4","key":"18068_CR44","doi-asserted-by":"publisher","first-page":"1903","DOI":"10.1109\/TCSVT.2021.3088505","volume":"32","author":"B Chen","year":"2022","unstructured":"Chen B, Zhu L, Li G, Lu F, Fan H, Wang S (2022) Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment. IEEE Trans Circuits Sys Video Technol 32(4):1903\u20131916. https:\/\/doi.org\/10.1109\/TCSVT.2021.3088505","journal-title":"IEEE Trans Circuits Sys Video Technol"},{"issue":"6","key":"18068_CR45","doi-asserted-by":"publisher","first-page":"3500","DOI":"10.1109\/TCSVT.2021.3114509","volume":"32","author":"Y Liu","year":"2022","unstructured":"Liu Y, Wu J, Li L, Dong W, Zhang J, Shi G (2022) Spatiotemporal Representation Learning for Blind Video Quality Assessment. IEEE Trans Circuits Sys Video Technol 32(6):3500\u20133513. https:\/\/doi.org\/10.1109\/TCSVT.2021.3114509","journal-title":"IEEE Trans Circuits Sys Video Technol"},{"issue":"4","key":"18068_CR46","doi-asserted-by":"publisher","first-page":"1238","DOI":"10.1007\/s11263-020-01408-w","volume":"129","author":"D Li","year":"2021","unstructured":"Li D, Jiang T, Jiang M (2021) Unified Quality Assessment of in-the-Wild Videos with Mixed Datasets Training. Int J Comput Vis 129(4):1238\u20131257. https:\/\/doi.org\/10.1007\/s11263-020-01408-w","journal-title":"Int J Comput Vis"},{"key":"18068_CR47","doi-asserted-by":"publisher","unstructured":"Vishwakarma AK, Bhurchandi KM (2022) No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion. J Vis Commun Image Represent 89. https:\/\/doi.org\/10.1016\/j.jvcir.2022.103676","DOI":"10.1016\/j.jvcir.2022.103676"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-18068-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-18068-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-18068-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,5]],"date-time":"2024-07-05T16:21:34Z","timestamp":1720196494000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-18068-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,11]]},"references-count":47,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["18068"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-18068-w","relation":{},"ISSN":["1573-7721"],"issn-type":[{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2024,1,11]]},"assertion":[{"value":"10 May 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 September 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 December 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 January 2024","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 that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}