{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:27:46Z","timestamp":1740122866534,"version":"3.37.3"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2022,10,8]],"date-time":"2022-10-08T00:00:00Z","timestamp":1665187200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,10,8]],"date-time":"2022-10-08T00:00:00Z","timestamp":1665187200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grants 61773127","U1911401 and 61727810"],"award-info":[{"award-number":["Grants 61773127","U1911401 and 61727810"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ten Thousand Talent Program approved in 2018"},{"name":"Guangdong Province Foundation","award":["Grants 2019B1515120036 and 501200069"],"award-info":[{"award-number":["Grants 2019B1515120036 and 501200069"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s11042-022-13918-5","type":"journal-article","created":{"date-parts":[[2022,10,8]],"date-time":"2022-10-08T06:03:50Z","timestamp":1665209030000},"page":"14837-14858","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["EAF-SR: an enhanced autoencoder framework for social recommendation"],"prefix":"10.1007","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3282-6785","authenticated-orcid":false,"given":"Taiheng","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaoshui","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,10,8]]},"reference":[{"key":"13918_CR1","doi-asserted-by":"crossref","unstructured":"Anil D, Vembar A, Hiriyannaiah S, Siddesh GM, Srinivasa KG (2018) Performance analysis of deep learning architectures for recommendation systems. In: Proceedings of the 25th IEEE International Conference on High Performance Computing Workshops (HiPCW), pp 129\u2013136","DOI":"10.1109\/HiPCW.2018.8634192"},{"issue":"5","key":"13918_CR2","first-page":"52036","volume":"1168","author":"R Bao","year":"2019","unstructured":"Bao R, Sun Y (2019) Top-N recommendation model based on SDAE. J Phys: Conf Ser 1168(5):52036\u201352045","journal-title":"J Phys: Conf Ser"},{"key":"13918_CR3","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.knosys.2013.03.012","volume":"46","author":"J Bobadilla","year":"2013","unstructured":"Bobadilla J, Ortega F, Hernando A, Guti\u00e9rrez A (2013) Recommender systems survey. Knowl-Based Syst 46:109\u2013132","journal-title":"Knowl-Based Syst"},{"key":"13918_CR4","doi-asserted-by":"crossref","unstructured":"Bottou L (2012) Stochastic gradient descent tricks. In: Proceedings of the neural networks: tricks of the trade, pp 421\u2013436","DOI":"10.1007\/978-3-642-35289-8_25"},{"issue":"2","key":"13918_CR5","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1109\/TKDE.2018.2881260","volume":"32","author":"Q Cui","year":"2020","unstructured":"Cui Q, Wu S, Liu Q, Zhong W, Wang L (2020) MV-RNN: a multi-view recurrent neural network for sequential recommendation. IEEE Trans Knowl Data Eng 32(2):317\u2013331","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"13918_CR6","doi-asserted-by":"publisher","first-page":"1279","DOI":"10.1016\/j.ins.2019.10.038","volume":"512","author":"A Da\u2019u","year":"2020","unstructured":"Da\u2019u A, Salim N, Rabiu I, Osman A (2020) Recommendation system exploiting aspect-based opinion mining with deep learning method. Inf Sci 512:1279\u20131292","journal-title":"Inf Sci"},{"issue":"5","key":"13918_CR7","doi-asserted-by":"publisher","first-page":"1164","DOI":"10.1109\/TNNLS.2016.2514368","volume":"28","author":"S Deng","year":"2016","unstructured":"Deng S, Huang L, Xu G, Wu X, Wu Z (2016) On deep learning for trust-aware recommendations in social networks. IEEE Trans Neur Netw Learn Syst 28(5):1164\u20131177","journal-title":"IEEE Trans Neur Netw Learn Syst"},{"key":"13918_CR8","doi-asserted-by":"crossref","unstructured":"Dighe P, Asaei A, Bourlard H (2018) Far-field ASR using low-rank and sparse soft targets from parallel data. In: Proceedings of the IEEE Spoken Language Technology Workshop (SLT), pp 581\u2013587","DOI":"10.1109\/SLT.2018.8639579"},{"issue":"4","key":"13918_CR9","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1109\/TSMC.2013.2263128","volume":"44","author":"M Eirinaki","year":"2013","unstructured":"Eirinaki M, Louta M D, Varlamis I (2013) A trust-aware system for personalized user recommendations in social networks. IEEE Trans Syst Man Cybern: Syst 44(4):409\u2013421","journal-title":"IEEE Trans Syst Man Cybern: Syst"},{"key":"13918_CR10","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.neunet.2017.02.013","volume":"92","author":"HM Fayek","year":"2017","unstructured":"Fayek H M, Lech M, Cavedon L (2017) Evaluating deep learning architectures for speech emotion recognition. Neural Netw 92:60\u201368","journal-title":"Neural Netw"},{"issue":"3","key":"13918_CR11","doi-asserted-by":"publisher","first-page":"1084","DOI":"10.1109\/TCYB.2018.2795041","volume":"49","author":"M Fu","year":"2018","unstructured":"Fu M, Qu H, Yi Z, Lu L, Liu Y (2018) A novel deep learning-based collaborative filtering model for recommendation system. IEEE Trans Cybern 49(3):1084\u20131096","journal-title":"IEEE Trans Cybern"},{"key":"13918_CR12","doi-asserted-by":"crossref","unstructured":"Guo G, Zhang J, Yorke-Smith N (2015) TrustSVD: collaborative filtering with both the explicit and implicit influence of user trust and of item ratings. In: Proceedings of the AAAI conference on artificial intelligence, vol 29, pp 123\u2013129","DOI":"10.1609\/aaai.v29i1.9153"},{"issue":"7","key":"13918_CR13","first-page":"38","volume":"14","author":"G Hinton","year":"2015","unstructured":"Hinton G, Vinyals O, Dean J (2015) Distilling the knowledge in a neural network. Comput Sci 14(7):38\u201339","journal-title":"Comput Sci"},{"key":"13918_CR14","doi-asserted-by":"publisher","first-page":"113724","DOI":"10.1016\/j.eswa.2020.113724","volume":"161","author":"A Jain","year":"2020","unstructured":"Jain A, Nagar S, Singh P K, Dhar J (2020) EMUCF: enhanced multistage user-based collaborative filtering through non-linear similarity for recommendation systems. Expert Syst Appl 161:113724","journal-title":"Expert Syst Appl"},{"key":"13918_CR15","doi-asserted-by":"crossref","unstructured":"Jamali M, Ester M (2010) A matrix factorization technique with trust propagation for recommendation in social networks. In: Proceedings of the 4th ACM conference on recommender systems, pp 135\u2013142","DOI":"10.1145\/1864708.1864736"},{"key":"13918_CR16","doi-asserted-by":"publisher","first-page":"40416","DOI":"10.1109\/ACCESS.2019.2897586","volume":"7","author":"Z Ji","year":"2019","unstructured":"Ji Z, Pi H, Wei W, Xiong B, Wo\u017aniak M, Damasevicius R (2019) Recommendation based on review texts and social communities: a hybrid model. IEEE Access 7:40416\u201340427","journal-title":"IEEE Access"},{"issue":"1","key":"13918_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1644873.1644874","volume":"4","author":"Y Koren","year":"2010","unstructured":"Koren Y (2010) Factor in the neighbors: scalable and accurate collaborative filtering. ACM Trans Knowl Discov Data (TKDD) 4(1):1\u201324","journal-title":"ACM Trans Knowl Discov Data (TKDD)"},{"key":"13918_CR18","doi-asserted-by":"crossref","unstructured":"Koren Y, Rendle S, Bell R (2022) Advances in collaborative filtering. Recommender Systems Handbook, 91\u2013142","DOI":"10.1007\/978-1-0716-2197-4_3"},{"key":"13918_CR19","doi-asserted-by":"crossref","unstructured":"Li X, She J (2017) Collaborative variational autoencoder for recommender systems. In: Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining, pp 305\u2013314","DOI":"10.1145\/3097983.3098077"},{"key":"13918_CR20","doi-asserted-by":"crossref","unstructured":"Li S, Kawale J, Fu Y (2015) Deep collaborative filtering via marginalized denoising auto-encoder. In: Proceedings of the 24th ACM international on conference on information and knowledge management, pp 811\u2013820","DOI":"10.1145\/2806416.2806527"},{"key":"13918_CR21","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.knosys.2017.02.032","volume":"127","author":"J Li","year":"2017","unstructured":"Li J, Chen C, Chen H, Tong C (2017) Towards context-aware social recommendation via individual trust. Knowl-Based Syst 127:58\u201366","journal-title":"Knowl-Based Syst"},{"key":"13918_CR22","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1016\/j.ins.2018.07.060","volume":"496","author":"H Li","year":"2019","unstructured":"Li H, Li K, An J, Zheng W, Li K (2019) An efficient manifold regularized sparse non-negative matrix factorization model for large-scale recommender systems on GPUs. Inf Sci 496:464\u2013484","journal-title":"Inf Sci"},{"key":"13918_CR23","doi-asserted-by":"crossref","unstructured":"Liang D, Krishnan R G, Hoffman M D, Jebara T (2018) Variational autoencoders for collaborative filtering. In: Proceedings of the 27th world wide web conference, pp 689\u2013698","DOI":"10.1145\/3178876.3186150"},{"key":"13918_CR24","doi-asserted-by":"crossref","unstructured":"Liu Z, Lin Y, Sun M (2020) Representation learning for natural language processing. Springer Nature, 1\u2013334","DOI":"10.1007\/978-981-15-5573-2_1"},{"issue":"2","key":"13918_CR25","doi-asserted-by":"publisher","first-page":"1273","DOI":"10.1109\/TII.2014.2308433","volume":"10","author":"X Luo","year":"2014","unstructured":"Luo X, Zhou M, Xia Y, Zhu Q (2014) An efficient non-negative matrix-factorization-based approach to collaborative filtering for recommender systems. IEEE Trans Industr Inf 10(2):1273\u20131284","journal-title":"IEEE Trans Industr Inf"},{"key":"13918_CR26","doi-asserted-by":"crossref","unstructured":"Ma H, Zhou D, Liu C, Lyu M R, King I (2011) Recommender systems with social regularization. In: Proceedings of the 4th ACM international conference on web search and data mining, pp 287\u2013296","DOI":"10.1145\/1935826.1935877"},{"issue":"4","key":"13918_CR27","doi-asserted-by":"publisher","first-page":"3884","DOI":"10.1109\/LRA.2019.2926223","volume":"4","author":"A Magassouba","year":"2019","unstructured":"Magassouba A, Sugiura K, Quoc A T, Kawai H (2019) Understanding natural language instructions for fetching daily objects using GAN-based multimodal target\u2013source classification. IEEE Robot Autom Lett 4(4):3884\u20133891","journal-title":"IEEE Robot Autom Lett"},{"issue":"2","key":"13918_CR28","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.zemedi.2018.12.003","volume":"29","author":"A Maier","year":"2019","unstructured":"Maier A, Syben C, Lasser T, Riess C (2019) A gentle introduction to deep learning in medical image processing. Z Med Phys 29(2):86\u2013101","journal-title":"Z Med Phys"},{"key":"13918_CR29","doi-asserted-by":"crossref","unstructured":"Massa P, Avesani P (2004) Trust-aware collaborative filtering for recommender systems. In: Proceedings of the move to meaningful internet systems: CoopIS, DOA, and ODBASE, OTM confederated international conferences, pp 492\u2013508","DOI":"10.1007\/978-3-540-30468-5_31"},{"issue":"7","key":"13918_CR30","doi-asserted-by":"publisher","first-page":"1763","DOI":"10.1109\/TKDE.2013.168","volume":"26","author":"X Qian","year":"2013","unstructured":"Qian X, Feng H, Zhao G, Mei T (2013) Personalized recommendation combining user interest and social circle. IEEE Trans Knowl Data Eng 26 (7):1763\u20131777","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"13918_CR31","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.physa.2016.05.025","volume":"461","author":"F Qian","year":"2016","unstructured":"Qian F, Zhao S, Tang J, Zhang Y (2016) SoRS: social recommendation using global rating reputation and local rating similarity. Physica A 461:61\u201372","journal-title":"Physica A"},{"key":"13918_CR32","doi-asserted-by":"crossref","unstructured":"Qiang R, Liang F, Yang J (2013) Exploiting ranking factorization machines for microblog retrieval. In: Proceedings of the 22nd ACM international conference on information & knowledge management, pp 1783\u20131788","DOI":"10.1145\/2505515.2505648"},{"key":"13918_CR33","unstructured":"Rendle S, Freudenthaler C, Gantner Z, Schmidt-Thieme L (2009) BPR: bayesian personalized ranking from implicit feedback. In: Proceedings of the 25th conference on uncertainty in artificial intelligence, Montreal, pp 452\u2013461"},{"issue":"3","key":"13918_CR34","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1109\/TAI.2021.3064901","volume":"1","author":"PK Roy","year":"2020","unstructured":"Roy P K, Chahar S (2020) Fake profile detection on social networking websites: a comprehensive review. IEEE Trans Artif Intell 1(3):271\u2013285","journal-title":"IEEE Trans Artif Intell"},{"key":"13918_CR35","doi-asserted-by":"publisher","first-page":"101386","DOI":"10.1016\/j.csl.2022.101386","volume":"75","author":"PK Roy","year":"2022","unstructured":"Roy P K, Bhawal S, Subalalitha C N (2022) Hate speech and offensive language detection in dravidian languages using deep ensemble framework. Comput Speech Lang 75:101386","journal-title":"Comput Speech Lang"},{"key":"13918_CR36","doi-asserted-by":"crossref","unstructured":"Salakhutdinov R, Mnih A, Hinton G (2007) Restricted boltzmann machines for collaborative filtering. In: Proceedings of the 24th international conference on machine learning, pp 791\u2013798","DOI":"10.1145\/1273496.1273596"},{"key":"13918_CR37","doi-asserted-by":"crossref","unstructured":"Sedhain S, Menon A K, Sanner S, Xie L (2015) AutoRec: autoencoders meet collaborative filtering. In: Proceedings of the 24th international conference on world wide web, pp 111\u2013112","DOI":"10.1145\/2740908.2742726"},{"issue":"2","key":"13918_CR38","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/s10660-019-09377-0","volume":"20","author":"S Shamshoddin","year":"2020","unstructured":"Shamshoddin S, Khader J, Gani S (2020) Predicting consumer preferences in electronic market based on IoT and social networks using deep learning based collaborative filtering techniques. Electron Commer Res 20(2):241\u2013258","journal-title":"Electron Commer Res"},{"issue":"5","key":"13918_CR39","first-page":"1906","volume":"33","author":"X Shen","year":"2021","unstructured":"Shen X, Yi B, Liu H, Zhang W, Zhang Z, Liu S, Xiong N (2021) Deep variational matrix factorization with knowledge embedding for recommendation system. IEEE Trans Knowl Data Eng 33(5):1906\u20131918","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"4","key":"13918_CR40","doi-asserted-by":"publisher","first-page":"1113","DOI":"10.1007\/s13278-013-0141-9","volume":"3","author":"J Tang","year":"2013","unstructured":"Tang J, Hu X, Liu H (2013) Social recommendation: a review. Soc Netw Anal Min 3(4):1113\u20131133","journal-title":"Soc Netw Anal Min"},{"key":"13918_CR41","doi-asserted-by":"crossref","unstructured":"Tuzhilin A (2010) Towards the next generation of recommender systems. In: Proceedings of the 1st International Conference on E-Business Intelligence (ICEBI2010), pp 553\u2013557","DOI":"10.2991\/icebi.2010.28"},{"key":"13918_CR42","doi-asserted-by":"crossref","unstructured":"Udendhran R, Balamurugan M, Suresh A, Varatharajan R (2020) Enhancing image processing architecture using deep learning for embedded vision systems. Microprocess Microsyst, 103094\u2013103101","DOI":"10.1016\/j.micpro.2020.103094"},{"key":"13918_CR43","doi-asserted-by":"crossref","unstructured":"Wang X, He X, Nie L, Chua T (2017) Item silk road: recommending items from information domains to social users. In: Proceedings of the 40th international ACM SIGIR conference on research and development in information retrieval, pp 185\u2013194","DOI":"10.1145\/3077136.3080771"},{"key":"13918_CR44","doi-asserted-by":"publisher","first-page":"82826","DOI":"10.1109\/ACCESS.2019.2924443","volume":"7","author":"X Wang","year":"2019","unstructured":"Wang X, Yang X, Guo L, Han Y, Liu F, Gao B (2019) Exploiting social review-enhanced convolutional matrix factorization for social recommendation. IEEE Access 7:82826\u201382837","journal-title":"IEEE Access"},{"key":"13918_CR45","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.eswa.2016.09.040","volume":"69","author":"J Wei","year":"2017","unstructured":"Wei J, He J, Chen K, Zhou Y, Tang Z (2017) Collaborative filtering and deep learning based recommendation system for cold start items. Expert Syst Appl 69:29\u201339","journal-title":"Expert Syst Appl"},{"issue":"6332","key":"13918_CR46","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1038\/352236a0","volume":"352","author":"BS Wilson","year":"1991","unstructured":"Wilson B S, Finley C C, Lawson D T, Wolford R D, Eddington D K, Rabinowitz W M (1991) Better speech recognition with cochlear implants. Nature 352(6332):236\u2013238","journal-title":"Nature"},{"key":"13918_CR47","doi-asserted-by":"crossref","unstructured":"Wu Y, DuBois C, Zheng A X, Ester M (2016) Collaborative denoising auto-encoders for top-N recommender systems. In: Proceedings of the 9th ACM international conference on web search and data mining, pp 153\u2013162","DOI":"10.1145\/2835776.2835837"},{"issue":"1","key":"13918_CR48","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1109\/TSMC.2018.2872842","volume":"51","author":"L Wu","year":"2021","unstructured":"Wu L, Sun P, Hong R, Ge Y, Wang M (2021) Collaborative neural social recommendation. IEEE Trans Syst Man Cybern: Syst 51(1):464\u2013476","journal-title":"IEEE Trans Syst Man Cybern: Syst"},{"key":"13918_CR49","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.neucom.2020.01.085","volume":"396","author":"X Wu","year":"2020","unstructured":"Wu X, Sahoo D, Hoi Steven CH (2020) Recent advances in deep learning for object detection. Neurocomputing 396:39\u201364","journal-title":"Neurocomputing"},{"issue":"8","key":"13918_CR50","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.1109\/TPAMI.2016.2605085","volume":"39","author":"B Yang","year":"2016","unstructured":"Yang B, Lei Y, Liu J, Li W (2016) Social collaborative filtering by trust. IEEE Trans Pattern Anal Mach Intell 39(8):1633\u20131647","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"13918_CR51","doi-asserted-by":"crossref","unstructured":"Zhang S, Yao L, Xu X (2017) AutoSVD++ an efficient hybrid collaborative filtering model via contractive auto-encoders. In: Proceedings of the 40th international ACM SIGIR conference on research and development in information retrieval, pp 957\u2013960","DOI":"10.1145\/3077136.3080689"},{"issue":"2","key":"13918_CR52","first-page":"1","volume":"40","author":"C Zhang","year":"2021","unstructured":"Zhang C, Wang Y, Zhu L, Song J, Yin H (2021) Multi-graph heterogeneous interaction fusion for social recommendation. ACM Trans Inform Syst 40 (2):1\u201326","journal-title":"ACM Trans Inform Syst"},{"issue":"2","key":"13918_CR53","doi-asserted-by":"publisher","first-page":"886","DOI":"10.1109\/TETC.2018.2870734","volume":"9","author":"P Zhang","year":"2021","unstructured":"Zhang P, Xiong F, Leung Hareton KN, Song W (2021) FunkR-pDAE: personalized project recommendation using deep learning. IEEE Trans Emerg Top Comput 9(2):886\u2013900","journal-title":"IEEE Trans Emerg Top Comput"},{"key":"13918_CR54","doi-asserted-by":"crossref","unstructured":"Zhao T, McAuley J, King I (2014) Leveraging social connections to improve personalized ranking for collaborative filtering. In: Proceedings of the 23rd ACM international conference on conference on information and knowledge management, pp 261\u2013270","DOI":"10.1145\/2661829.2661998"},{"issue":"9","key":"13918_CR55","doi-asserted-by":"publisher","first-page":"2522","DOI":"10.1109\/TKDE.2016.2569096","volume":"28","author":"Z Zhao","year":"2016","unstructured":"Zhao Z, Lu H, Cai D, He X, Zhuang Y (2016) User preference learning for online social recommendation. IEEE Trans Knowl Data Eng 28(9):2522\u20132534","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"13918_CR56","doi-asserted-by":"publisher","unstructured":"Zhao H, Sun X, Dong J, Chen C, Dong Z (2020) Highlight every step: knowledge distillation via collaborative teaching. IEEE Transactions on Cybernetics, https:\/\/doi.org\/10.1109\/TCYB.2020.3007506","DOI":"10.1109\/TCYB.2020.3007506"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13918-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-13918-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-13918-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T11:40:28Z","timestamp":1679658028000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-13918-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,8]]},"references-count":56,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["13918"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-13918-5","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2022,10,8]]},"assertion":[{"value":"6 August 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 June 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 September 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 October 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflict of Interests"}}]}}