{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T05:07:48Z","timestamp":1750223268919,"version":"3.37.3"},"reference-count":67,"publisher":"Springer Science and Business Media LLC","license":[{"start":{"date-parts":[[2022,7,5]],"date-time":"2022-07-05T00:00:00Z","timestamp":1656979200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,7,5]],"date-time":"2022-07-05T00:00:00Z","timestamp":1656979200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61802380"],"award-info":[{"award-number":["61802380"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"DOI":"10.1007\/s10489-022-03845-1","type":"journal-article","created":{"date-parts":[[2022,7,5]],"date-time":"2022-07-05T06:02:50Z","timestamp":1657000970000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Cross modification attention-based deliberation model for image captioning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0682-7589","authenticated-orcid":false,"given":"Zheng","family":"Lian","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haichang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohui","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,5]]},"reference":[{"issue":"4","key":"3845_CR1","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1109\/TPAMI.2016.2587640","volume":"39","author":"O Vinyals","year":"2016","unstructured":"Vinyals O, Toshev A, Bengio S, Erhan D (2016) Show and tell: lessons learned from the 2015 mscoco image captioning challenge. IEEE Trans Pattern Anal Mach Intell 39(4):652\u2013663","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3845_CR2","unstructured":"Xu K, Ba J, Kiros R, Cho K, Courville A, Salakhudinov R, Zemel R, Bengio Y (2015) Show, attend and tell: neural image caption generation with visual attention. In: International conference on machine learning. PMLR, pp 2048\u20132057"},{"key":"3845_CR3","doi-asserted-by":"crossref","unstructured":"Anderson P, He X, Buehler C, Teney D, Johnson M, Gould S, Zhang L (2018) Bottom-up and top-down attention for image captioning and visual question answering. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 6077\u20136086","DOI":"10.1109\/CVPR.2018.00636"},{"key":"3845_CR4","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.neucom.2018.10.059","volume":"330","author":"A Yuan","year":"2019","unstructured":"Yuan A, Li X, Lu X (2019) 3g structure for image caption generation. Neurocomputing 330:17\u201328","journal-title":"Neurocomputing"},{"issue":"8","key":"3845_CR5","doi-asserted-by":"publisher","first-page":"2149","DOI":"10.1109\/TMM.2019.2951226","volume":"22","author":"L Guo","year":"2019","unstructured":"Guo L, Liu J, Lu S, Lu H (2019) Show, tell, and polish: ruminant decoding for image captioning. IEEE Trans Multimed 22(8):2149\u20132162","journal-title":"IEEE Trans Multimed"},{"key":"3845_CR6","doi-asserted-by":"crossref","unstructured":"Pan Y, Yao T, Li Y, Mei T (2020) X-linear attention networks for image captioning. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 10971\u201310980","DOI":"10.1109\/CVPR42600.2020.01098"},{"key":"3845_CR7","doi-asserted-by":"crossref","unstructured":"Yang X, Zhang H, Cai J (2020) Auto-encoding and distilling scene graphs for image captioning. IEEE Trans Pattern Anal Mach Intell","DOI":"10.1109\/TPAMI.2020.3042192"},{"key":"3845_CR8","doi-asserted-by":"crossref","unstructured":"Song Z, Zhou X, Mao Z, Tan J (2021) Image captioning with context-aware auxiliary guidance. In: AAAI","DOI":"10.1609\/aaai.v35i3.16361"},{"key":"3845_CR9","doi-asserted-by":"crossref","unstructured":"Zhou D, Yang J, Bao R (2021) Collaborative strategy network for spatial attention image captioning. Appl Intell:1\u201316","DOI":"10.1007\/s10489-021-02943-w"},{"key":"3845_CR10","doi-asserted-by":"crossref","unstructured":"Luo Y, Ji J, Sun X, Cao L, Wu Y, Huang F, Lin C-W, Ji R (2021) Dual-level collaborative transformer for image captioning. In: Proceedings of the AAAI conference on artificial intelligence, vol 35, pp 2286\u20132293","DOI":"10.1609\/aaai.v35i3.16328"},{"key":"3845_CR11","doi-asserted-by":"crossref","unstructured":"Yu L, Zhang J, Wu Q (2021) Dual attention on pyramid feature maps for image captioning. IEEE Trans Multimed","DOI":"10.1109\/TMM.2021.3072479"},{"key":"3845_CR12","doi-asserted-by":"crossref","unstructured":"Ben H, Pan Y, Li Y, Yao T, Hong R, Wang M, Mei T (2021) Unpaired image captioning with semantic-constrained self-learning. IEEE Trans Multimedia","DOI":"10.1109\/TMM.2021.3060948"},{"key":"3845_CR13","doi-asserted-by":"publisher","first-page":"2450","DOI":"10.1109\/TIP.2021.3051476","volume":"30","author":"H Liu","year":"2021","unstructured":"Liu H, Zhang S, Lin K, Wen J, Li J, Hu X (2021) Vocabulary-wide credit assignment for training image captioning models. IEEE Trans Image Process 30:2450\u20132460","journal-title":"IEEE Trans Image Process"},{"key":"3845_CR14","doi-asserted-by":"crossref","unstructured":"Xian T, Li Z, Zhang C, Ma H (2022) Dual global enhanced transformer for image captioning. Neural Netw","DOI":"10.1016\/j.neunet.2022.01.011"},{"key":"3845_CR15","doi-asserted-by":"crossref","unstructured":"Shao J, Yang R (2022) Controllable image caption with an encoder-decoder optimization structure. Appl Intell:1\u201312","DOI":"10.1007\/s10489-021-02988-x"},{"key":"3845_CR16","doi-asserted-by":"crossref","unstructured":"Yao T, Pan Y, Li Y, Mei T (2018) Exploring visual relationship for image captioning. In: Proceedings of the European conference on computer vision (ECCV), pp 684\u2013699","DOI":"10.1007\/978-3-030-01264-9_42"},{"key":"3845_CR17","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.neucom.2018.08.069","volume":"319","author":"X Zhu","year":"2018","unstructured":"Zhu X, Li L, Liu J, Li Z, Peng H, Niu X (2018) Image captioning with triple-attention and stack parallel lstm. Neurocomputing 319:55\u201365","journal-title":"Neurocomputing"},{"key":"3845_CR18","doi-asserted-by":"crossref","unstructured":"Huang L, Wang W, Chen J, Wei X-Y (2019) Attention on attention for image captioning. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 4634\u20134643","DOI":"10.1109\/ICCV.2019.00473"},{"key":"3845_CR19","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1016\/j.neucom.2019.04.095","volume":"398","author":"S Ding","year":"2020","unstructured":"Ding S, Qu S, Xi Y, Wan S (2020) Stimulus-driven and concept-driven analysis for image caption generation. Neurocomputing 398:520\u2013530","journal-title":"Neurocomputing"},{"key":"3845_CR20","doi-asserted-by":"crossref","unstructured":"Wang C, Gu X (2021) Image captioning with adaptive incremental global context attention. Appl Intell:1\u201323","DOI":"10.1007\/s10489-021-02734-3"},{"key":"3845_CR21","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez A N, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. In: Advances in neural information processing systems, pp 5998\u20136008"},{"key":"3845_CR22","unstructured":"Dauphin YN, Fan A, Auli M, Grangier D (2017) Language modeling with gated convolutional networks. In: International conference on machine learning. PMLR, pp 933\u2013941"},{"key":"3845_CR23","doi-asserted-by":"crossref","unstructured":"Sammani F, Melas-Kyriazi L (2020) Show, edit and tell: a framework for editing image captions. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 4808\u20134816","DOI":"10.1109\/CVPR42600.2020.00486"},{"key":"3845_CR24","volume-title":"Elements of information theory","author":"TM Cover","year":"2012","unstructured":"Cover TM, Thomas JA (2012) Elements of information theory. Wiley, New York"},{"key":"3845_CR25","doi-asserted-by":"crossref","unstructured":"Lin T-Y, Maire M, Belongie S, Hays J, Perona P, Ramanan D, Doll\u00e1r P, Zitnick CL (2014) Microsoft coco: common objects in context. In: European conference on computer vision. Springer, pp 740\u2013755","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"3845_CR26","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1162\/tacl_a_00166","volume":"2","author":"P Young","year":"2014","unstructured":"Young P, Lai A, Hodosh M, Hockenmaier J (2014) From image descriptions to visual denotations: new similarity metrics for semantic inference over event descriptions. Trans Assoc Comput Linguist 2:67\u201378","journal-title":"Trans Assoc Comput Linguist"},{"key":"3845_CR27","doi-asserted-by":"crossref","unstructured":"Yang X, Tang K, Zhang H, Cai J (2019) Auto-encoding scene graphs for image captioning. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 10685\u201310694","DOI":"10.1109\/CVPR.2019.01094"},{"key":"3845_CR28","doi-asserted-by":"crossref","unstructured":"Gu J, Wang G, Cai J, Chen T (2017) An empirical study of language cnn for image captioning. In: Proceedings of the IEEE international conference on computer vision, pp 1222\u2013 1231","DOI":"10.1109\/ICCV.2017.138"},{"key":"3845_CR29","doi-asserted-by":"crossref","unstructured":"Aneja J, Deshpande A, Schwing A G (2018) Convolutional image captioning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5561\u20135570","DOI":"10.1109\/CVPR.2018.00583"},{"key":"3845_CR30","doi-asserted-by":"crossref","unstructured":"Qin Y, Du J, Zhang Y, Lu H (2019) Look back and predict forward in image captioning. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8367\u20138375","DOI":"10.1109\/CVPR.2019.00856"},{"key":"3845_CR31","doi-asserted-by":"crossref","unstructured":"Cho K, Van Merri\u00ebnboer B, Gulcehre C, Bahdanau D, Bougares F, Schwenk H, Bengio Y (2014) Learning phrase representations using rnn encoder-decoder for statistical machine translation. In: Proceedings of the 2014. Conference on empirical methods in natural language processing, Doha, Qatar, pp 25\u201329","DOI":"10.3115\/v1\/D14-1179"},{"key":"3845_CR32","unstructured":"Sutskever I, Vinyals O, Le QV (2014) Sequence to sequence learning with neural networks. In: Advances in neural information processing systems, pp 3104\u20133112"},{"issue":"8","key":"3845_CR33","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"key":"3845_CR34","unstructured":"Bahdanau D, Cho KH, Bengio Y (2015) Neural machine translation by jointly learning to align and translate. In: 3rd international conference on learning representations, ICLR 2015"},{"key":"3845_CR35","doi-asserted-by":"crossref","unstructured":"Lu J, Xiong C, Parikh D, Socher R (2017) Knowing when to look: adaptive attention via a visual sentinel for image captioning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 375\u2013383","DOI":"10.1109\/CVPR.2017.345"},{"key":"3845_CR36","first-page":"91","volume":"28","author":"S Ren","year":"2015","unstructured":"Ren S, He K, Girshick R, Sun J (2015) Faster r-cnn: towards real-time object detection with region proposal networks. Adv Neural Inf Process Syst 28:91\u201399","journal-title":"Adv Neural Inf Process Syst"},{"key":"3845_CR37","doi-asserted-by":"crossref","unstructured":"Chen S, Zhao Q (2018) Boosted attention: leveraging human attention for image captioning. In: Proceedings of the European conference on computer vision (ECCV), pp 68\u201384","DOI":"10.1007\/978-3-030-01252-6_5"},{"key":"3845_CR38","doi-asserted-by":"crossref","unstructured":"Hao Y, Zhang Y, Liu K, He S, Liu Z, Wu H, Zhao J (2017) An end-to-end model for question answering over knowledge base with cross-attention combining global knowledge. In: Proceedings of the 55th annual meeting of the association for computational linguistics (Volume 1: Long Papers), pp 221\u2013231","DOI":"10.18653\/v1\/P17-1021"},{"key":"3845_CR39","doi-asserted-by":"crossref","unstructured":"Lee K-H, Chen X, Hua G, Hu H, He X (2018) Stacked cross attention for image-text matching. In: Proceedings of the European conference on computer vision (ECCV), pp 201\u2013216","DOI":"10.1007\/978-3-030-01225-0_13"},{"key":"3845_CR40","first-page":"1784","volume":"30","author":"Y Xia","year":"2017","unstructured":"Xia Y, Tian F, Wu L, Lin J, Qin T, Yu N, Liu T-Y (2017) Deliberation networks: sequence generation beyond one-pass decoding. Adv Neural Inf Process Syst 30:1784\u20131794","journal-title":"Adv Neural Inf Process Syst"},{"key":"3845_CR41","doi-asserted-by":"crossref","unstructured":"Hu K, Sainath TN, Pang R, Prabhavalkar R (2020) Deliberation model based two-pass end-to-end speech recognition. In: ICASSP 2020-2020 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 7799\u20137803","DOI":"10.1109\/ICASSP40776.2020.9053606"},{"key":"3845_CR42","doi-asserted-by":"crossref","unstructured":"Hu K, Pang R, Sainath TN, Strohman T (2021) Transformer based deliberation for two-pass speech recognition. In: 2021 IEEE spoken language technology workshop (SLT). IEEE, pp 68\u201374","DOI":"10.1109\/SLT48900.2021.9383497"},{"key":"3845_CR43","first-page":"2361","volume":"29","author":"Z Yang","year":"2016","unstructured":"Yang Z, Yuan Y, Wu Y, Cohen WW, Salakhutdinov RR (2016) Review networks for caption generation. Adv Neural Inf Process Syst 29:2361\u20132369","journal-title":"Adv Neural Inf Process Syst"},{"key":"3845_CR44","doi-asserted-by":"crossref","unstructured":"Gao L, Fan K, Song J, Liu X, Xu X, Shen HT (2019) Deliberate attention networks for image captioning. In: Proceedings of the AAAI conference on artificial intelligence, vol 33, pp 8320\u20138327","DOI":"10.1609\/aaai.v33i01.33018320"},{"key":"3845_CR45","unstructured":"Sammani F, Elsayed M (2019) Look and modify: modification networks for image captioning. British Machine Vision Conference(BMVC)"},{"key":"3845_CR46","unstructured":"Ranzato M, Chopra S, Auli M, Zaremba W (2016) Sequence level training with recurrent neural networks. In: 4th international conference on learning representations, ICLR 2016"},{"key":"3845_CR47","unstructured":"Zhang L, Sung F, Feng L, Xiang T, Gong S, Yang Y, Hospedales T (2017) Actor-critic sequence training for image captioning. In: Visually-grounded interaction and language (viGIL): NIPS 2017 workshop"},{"key":"3845_CR48","doi-asserted-by":"crossref","unstructured":"Rennie S J, Marcheret E, Mroueh Y, Ross J, Goel V (2017) Self-critical sequence training for image captioning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7008\u20137024","DOI":"10.1109\/CVPR.2017.131"},{"key":"3845_CR49","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"3845_CR50","unstructured":"Glorot X, Bordes A, Bengio Y (2011) Deep sparse rectifier neural networks. In: Proceedings of the fourteenth international conference on artificial intelligence and statistics, pp 315\u2013323. JMLR Workshop and Conference Proceedings"},{"key":"3845_CR51","doi-asserted-by":"crossref","unstructured":"Vedantam R, Lawrence Zitnick C, Parikh D (2015) Cider: Consensus-based image description evaluation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4566\u20134575","DOI":"10.1109\/CVPR.2015.7299087"},{"key":"3845_CR52","unstructured":"Ng AY, Harada D, Russell S (1999) Policy invariance under reward transformations: theory and application to reward shaping. In: Icml, vol 99, pp 278\u2013287"},{"issue":"1","key":"3845_CR53","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1007\/s11263-016-0981-7","volume":"123","author":"R Krishna","year":"2017","unstructured":"Krishna R, Zhu Y, Groth O, Johnson J, Hata K, Kravitz J, Chen S, Kalantidis Y, Li L-J, Shamma DA et al (2017) Visual genome: connecting language and vision using crowdsourced dense image annotations. Int J Comput Vis 123(1):32\u201373","journal-title":"Int J Comput Vis"},{"key":"3845_CR54","doi-asserted-by":"crossref","unstructured":"Karpathy A, Fei-Fei L (2015) Deep visual-semantic alignments for generating image descriptions. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3128\u20133137","DOI":"10.1109\/CVPR.2015.7298932"},{"key":"3845_CR55","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":"3845_CR56","doi-asserted-by":"crossref","unstructured":"Denkowski M, Lavie A (2014) Meteor universal: language specific translation evaluation for any target language. In: Proceedings of the ninth workshop on statistical machine translation, pp 376\u2013380","DOI":"10.3115\/v1\/W14-3348"},{"key":"3845_CR57","unstructured":"Lin C-Y (2004) Rouge: a package for automatic evaluation of summaries. In: Text summarization branches out, pp 74\u201381"},{"key":"3845_CR58","doi-asserted-by":"crossref","unstructured":"Anderson P, Fernando B, Johnson M, Gould S (2016) Spice: Semantic propositional image caption evaluation. In: European conference on computer vision. Springer, pp 382\u2013398","DOI":"10.1007\/978-3-319-46454-1_24"},{"key":"3845_CR59","doi-asserted-by":"crossref","unstructured":"Cornia M, Stefanini M, Baraldi L, Cucchiara R (2020) Meshed-memory transformer for image captioning. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 10578\u201310587","DOI":"10.1109\/CVPR42600.2020.01059"},{"key":"3845_CR60","doi-asserted-by":"crossref","unstructured":"Song Z, Zhou X, Mao Z, Tan J (2021) Image captioning with context-aware auxiliary guidance. In: Proceedings of the AAAI conference on artificial intelligence, vol 35, pp 2584\u20132592","DOI":"10.1609\/aaai.v35i3.16361"},{"key":"3845_CR61","doi-asserted-by":"crossref","unstructured":"Szegedy C, Vanhoucke V, Ioffe S, Shlens J, Wojna Z (2016) Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2818\u20132826","DOI":"10.1109\/CVPR.2016.308"},{"key":"3845_CR62","unstructured":"Bengio S, Vinyals O, Jaitly N, Shazeer N (2015) Scheduled sampling for sequence prediction with recurrent neural networks. Adv Neural Inf Process Syst 28"},{"key":"3845_CR63","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.neucom.2018.02.106","volume":"328","author":"X He","year":"2019","unstructured":"He X, Yang Y, Shi B, Bai X (2019) Vd-san: visual-densely semantic attention network for image caption generation. Neurocomputing 328:48\u201355","journal-title":"Neurocomputing"},{"key":"3845_CR64","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1109\/TMM.2020.2976552","volume":"23","author":"J Zhang","year":"2021","unstructured":"Zhang J, Mei K, Zheng Y, Fan J (2021) Integrating part of speech guidance for image captioning. IEEE Trans Multimed 23:92\u2013104. https:\/\/doi.org\/10.1109\/TMM.2020.2976552","journal-title":"IEEE Trans Multimed"},{"issue":"2","key":"3845_CR65","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3439734","volume":"17","author":"H Wei","year":"2021","unstructured":"Wei H, Li Z, Huang F, Zhang C, Ma H, Shi Z (2021) Integrating scene semantic knowledge into image captioning. ACM Trans Multimed Comput Commun Appl (TOMM) 17(2):1\u201322","journal-title":"ACM Trans Multimed Comput Commun Appl (TOMM)"},{"key":"3845_CR66","doi-asserted-by":"crossref","unstructured":"Zhang X, Sun X, Luo Y, Ji J, Zhou Y, Wu Y, Huang F, Ji R (2021) Rstnet: captioning with adaptive attention on visual and non-visual words. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 15465\u201315474","DOI":"10.1109\/CVPR46437.2021.01521"},{"key":"3845_CR67","doi-asserted-by":"crossref","unstructured":"Yang X, Zhang H, Qi G, Cai J (2021) Causal attention for vision-language tasks. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 9847\u2013 9857","DOI":"10.1109\/CVPR46437.2021.00972"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03845-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-022-03845-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-022-03845-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,10]],"date-time":"2023-02-10T21:07:52Z","timestamp":1676063272000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-022-03845-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,5]]},"references-count":67,"alternative-id":["3845"],"URL":"https:\/\/doi.org\/10.1007\/s10489-022-03845-1","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2022,7,5]]},"assertion":[{"value":"1 June 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 July 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 there is no conflict of interests regarding the publication of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}