{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T19:04:43Z","timestamp":1759777483561,"version":"3.37.3"},"reference-count":53,"publisher":"Springer Science and Business Media LLC","issue":"21","license":[{"start":{"date-parts":[[2024,1,3]],"date-time":"2024-01-03T00:00:00Z","timestamp":1704240000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,3]],"date-time":"2024-01-03T00:00:00Z","timestamp":1704240000000},"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":["61873086"],"award-info":[{"award-number":["61873086"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Science and Technology Support Program of Changzhou","award":["CE20215022"],"award-info":[{"award-number":["CE20215022"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17948-5","type":"journal-article","created":{"date-parts":[[2024,1,3]],"date-time":"2024-01-03T05:02:45Z","timestamp":1704258165000},"page":"60003-60025","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An improved sequential recommendation model based on spatial self-attention mechanism and meta learning"],"prefix":"10.1007","volume":"83","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7130-8331","authenticated-orcid":false,"given":"Jianjun","family":"Ni","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tong","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangyi","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengfei","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon X.","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,3]]},"reference":[{"issue":"11","key":"17948_CR1","doi-asserted-by":"crossref","first-page":"16599","DOI":"10.1007\/s11042-020-08884-9","volume":"80","author":"T Trinh","year":"2021","unstructured":"Trinh T, Wu D, Wang R, Huang JZ (2021) An effective content-based event recommendation model. Multimed Tools Appl 80(11):16599\u201316618","journal-title":"Multimed Tools Appl"},{"issue":"4","key":"17948_CR2","doi-asserted-by":"crossref","first-page":"3109","DOI":"10.1007\/s12652-021-03438-9","volume":"14","author":"M Casillo","year":"2023","unstructured":"Casillo M, Colace F, Conte D, Lombardi M, Santaniello D, Valentino C (2023) Context-aware recommender systems and cultural heritage: a survey. J Ambient Intell Humaniz Comput 14(4):3109\u20133127","journal-title":"J Ambient Intell Humaniz Comput"},{"issue":"1","key":"17948_CR3","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1109\/TR.2022.3171309","volume":"72","author":"C Tao","year":"2022","unstructured":"Tao C, Lin K, Huang Z, Sun X (2022) Cram: Code recommendation with programming context based on self-attention mechanism. IEEE Trans Reliab 72(1):302\u2013316","journal-title":"IEEE Trans Reliab"},{"key":"17948_CR4","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.ins.2016.09.022","volume":"374","author":"F Narducci","year":"2016","unstructured":"Narducci F, Basile P, Musto C, Lops P, Caputo A, de Gemmis M, Iaquinta L, Semeraro G (2016) Concept-based item representations for a cross-lingual content-based recommendation process. Inf Sci 374:15\u201331","journal-title":"Inf Sci"},{"issue":"25","key":"17948_CR5","doi-asserted-by":"crossref","first-page":"35693","DOI":"10.1007\/s11042-021-11883-z","volume":"81","author":"T Anwar","year":"2022","unstructured":"Anwar T, Uma V, Hussain MI, Pantula M (2022) Collaborative filtering and knn based recommendation to overcome cold start and sparsity issues: a comparative analysis. Multimed Tools Appl 81(25):35693\u201335711","journal-title":"Multimed Tools Appl"},{"issue":"20","key":"17948_CR6","doi-asserted-by":"crossref","first-page":"9554","DOI":"10.3390\/app11209554","volume":"11","author":"J Ni","year":"2021","unstructured":"Ni J, Cai Y, Tang G, Xie Y (2021) Collaborative filtering recommendation algorithm based on TF-IDF and user characteristics. Appl Sci 11(20):9554","journal-title":"Appl Sci"},{"issue":"8","key":"17948_CR7","doi-asserted-by":"crossref","first-page":"11319","DOI":"10.1007\/s12652-023-04647-0","volume":"14","author":"SH Park","year":"2023","unstructured":"Park SH, Kim K (2023) Collaborative filtering recommendation system based on improved jaccard similarity. J Ambient Intell Humaniz Comput 14(8):11319\u201311336","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"17948_CR8","doi-asserted-by":"crossref","unstructured":"Hidasi Bz, Karatzoglou A (2018) Recurrent neural networks with top-k gains for session-based recommendations. In: Proceedings of the 27th ACM international conference on information and knowledge management, pp 843\u2013852","DOI":"10.1145\/3269206.3271761"},{"key":"17948_CR9","doi-asserted-by":"crossref","first-page":"4275868","DOI":"10.1155\/2022\/4275868","volume":"2022","author":"J Ni","year":"2022","unstructured":"Ni J, Tang G, Shen T, Cai Y, Cao W et al (2022) An improved sequential recommendation algorithm based on short-sequence enhancement and temporal self-attention mechanism. Complexity 2022:4275868","journal-title":"Complexity"},{"key":"17948_CR10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2021.3090410","volume":"60","author":"UA Bhatti","year":"2022","unstructured":"Bhatti UA, Yu Z, Chanussot J, Zeeshan Z, Yuan L, Luo W, Nawaz SA, Bhatti MA, Ain QU, Mehmood A (2022) Local similarity-based spatialspectral fusion hyperspectral image classification with deep cnn and gabor filtering. IEEE Trans Geosci Remote Sens 60:1\u201315","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"11","key":"17948_CR11","doi-asserted-by":"crossref","first-page":"15635","DOI":"10.1007\/s11042-022-12231-5","volume":"81","author":"Z Li","year":"2022","unstructured":"Li Z, XiaoBo C (2022) Recommendation algorithm of influence and trust relationship. Multimed Tools Appl 81(11):15635\u201315652","journal-title":"Multimed Tools Appl"},{"issue":"1","key":"17948_CR12","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1109\/MIC.2003.1167344","volume":"7","author":"G Linden","year":"2003","unstructured":"Linden G, Smith B, York J (2003) Amazon. com recommendations: item-to-item collaborative filtering. IEEE Internet computing 7(1):76\u201380","journal-title":"IEEE Internet computing"},{"key":"17948_CR13","doi-asserted-by":"crossref","first-page":"1041514","DOI":"10.3389\/fpls.2022.1041514","volume":"13","author":"SA Nawaz","year":"2022","unstructured":"Nawaz SA, Li J, Bhatti UA, Shoukat MU, Ahmad RM (2022) Ai-based object detection latest trends in remote sensing, multimedia and agriculture applications. Front Plant Sci 13:1041514","journal-title":"Front Plant Sci"},{"key":"17948_CR14","doi-asserted-by":"crossref","first-page":"118823","DOI":"10.1016\/j.eswa.2022.118823","volume":"213","author":"M Etemadi","year":"2023","unstructured":"Etemadi M, Bazzaz Abkenar S, Ahmadzadeh A, Haghi Kashani M, Asghari P, Akbari M, Mahdipour E (2023) A systematic review of healthcare recommender systems: open issues, challenges, and techniques. Expert Syst Appl 213:118823","journal-title":"Expert Syst Appl"},{"key":"17948_CR15","unstructured":"Finn C, Abbeel P, Levine S (2017) Model-agnostic meta-learning for fast adaptation of deep networks. In: 34th International conference on machine learning, ICML 2017, vol 3, pp 1856\u20131868"},{"issue":"19","key":"17948_CR16","doi-asserted-by":"crossref","first-page":"16255","DOI":"10.1007\/s00521-022-07302-5","volume":"34","author":"X Chu","year":"2022","unstructured":"Chu X, Wang J, Li S, Chai Y, Guo Y (2022) Empirical study on meta-feature characterization for multi-objective optimization problems. Neural Comput Appl 34(19):16255\u201316273","journal-title":"Neural Comput Appl"},{"key":"17948_CR17","doi-asserted-by":"crossref","unstructured":"Du Y, Zhu X, Chen L, Fang Z, Gao Y (2022) Metakg: meta-learning on knowledge graph for cold-start recommendation. IEEE Trans Knowl Data Eng","DOI":"10.1109\/TKDE.2022.3168775"},{"key":"17948_CR18","doi-asserted-by":"crossref","unstructured":"He R, Kang W-C, McAuley J (2017) Translation-based recommendation. In: Proceedings of the eleventh ACM conference on recommender systems, Como, Italy, pp 161\u2013169","DOI":"10.1145\/3109859.3109882"},{"key":"17948_CR19","doi-asserted-by":"crossref","unstructured":"Wang J, Ding K, Caverlee J (2021) Sequential recommendation for cold-start users with meta transitional learning. In: SIGIR 2021 - Proceedings of the 44th International ACM SIGIR conference on research and development in information retrieval, pp 1783\u20131787","DOI":"10.1145\/3404835.3463089"},{"issue":"12","key":"17948_CR20","first-page":"8693","volume":"35","author":"P Yin","year":"2023","unstructured":"Yin P, Ji D, Yan H, Gan H, Zhang J (2023) Multimodal deep collaborative filtering recommendation based on dual attention. Neural Comput Appl 35(12):8693\u20138706","journal-title":"Neural Comput Appl"},{"issue":"4 PART 2","key":"17948_CR21","doi-asserted-by":"crossref","first-page":"2065","DOI":"10.1016\/j.eswa.2013.09.005","volume":"41","author":"B Lika","year":"2014","unstructured":"Lika B, Kolomvatsos K, Hadjiefthymiades S (2014) Facing the cold start problem in recommender systems. Expert Syst Appl 41(4 PART 2):2065\u20132073","journal-title":"Expert Syst Appl"},{"issue":"7","key":"17948_CR22","doi-asserted-by":"crossref","first-page":"1888","DOI":"10.1109\/TMM.2017.2779043","volume":"20","author":"Y Yang","year":"2018","unstructured":"Yang Y, Xu Y, Wang E, Han J, Yu Z (2018) Improving existing collaborative filtering recommendations via serendipity-based algorithm. IEEE Trans Multimed 20(7):1888\u20131900","journal-title":"IEEE Trans Multimed"},{"issue":"4","key":"17948_CR23","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1109\/JAS.2015.7296535","volume":"2","author":"S Gao","year":"2015","unstructured":"Gao S, Yu Z, Shi L, Yan X, Song H (2015) Review expert collaborative recommendation algorithm based on topic relationship. IEEE\/CAA J Autom Sin 2(4):403\u2013411","journal-title":"IEEE\/CAA J Autom Sin"},{"key":"17948_CR24","unstructured":"Vartak M, Thiagarajan A, Miranda C, Bratman J, Larochelle H (2017) A meta-learning perspective on cold-start recommendations for items. In: 31st Annual conference on neural information processing systems, NIPS 2017, vol 30, pp 6905\u20136915"},{"key":"17948_CR25","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.neucom.2023.02.051","volume":"533","author":"I ur Rehman","year":"2023","unstructured":"ur Rehman I, Ali W, Jan Z, Ali Z, Xu H, Shao J (2023) Caml Contextual augmented meta-learning for cold-start recommendation. Neurocomputing 533:178\u2013190","journal-title":"Neurocomputing"},{"key":"17948_CR26","doi-asserted-by":"crossref","first-page":"115144","DOI":"10.1016\/j.apenergy.2020.115144","volume":"270","author":"W Li","year":"2020","unstructured":"Li W, Gong G, Fan H, Peng P, Chun L (2020) Meta-learning strategy based on user preferences and a machine recommendation system for real-time cooling load and cop forecasting. Appl Energy 270:115144","journal-title":"Appl Energy"},{"key":"17948_CR27","doi-asserted-by":"crossref","unstructured":"Xia Y, Luo J, Lan M, Zhou G, Li Z, Liu S (2022) Reason more like human: incorporating meta information into hierarchical reinforcement learning for knowledge graph reasoning. Appl Intell 1\u201316","DOI":"10.1007\/s10489-022-04147-2"},{"key":"17948_CR28","first-page":"5006915","volume":"72","author":"J Ni","year":"2023","unstructured":"Ni J, Shen K, Chen Y, Yang SX (2023) An improved ssd-like deep network-based object detection method for indoor scenes. IEEE Trans Instrum Meas 72:5006915","journal-title":"IEEE Trans Instrum Meas"},{"key":"17948_CR29","doi-asserted-by":"crossref","first-page":"5456","DOI":"10.3390\/app11125456","volume":"11","author":"E Mutabazi","year":"2021","unstructured":"Mutabazi E, Ni J, Tang G, Cao W (2021) A review on medical textual question answering systems based on deep learning approaches. Appl Sci-Basel 11:5456","journal-title":"Appl Sci-Basel"},{"key":"17948_CR30","doi-asserted-by":"crossref","first-page":"2749","DOI":"10.3390\/app10082749","volume":"10","author":"J Ni","year":"2020","unstructured":"Ni J, Chen Y, Chen Y, Zhu J, Ali D, Cao W (2020) A survey on theories and applications for self-driving cars based on deep learning methods. Appl Sci-Basel 10:2749","journal-title":"Appl Sci-Basel"},{"key":"17948_CR31","first-page":"5001614","volume":"71","author":"J Ni","year":"2022","unstructured":"Ni J, Shen K, Chen Y, Cao W, Yang SX (2022) An improved deep network-based scene classification method for self-driving cars. IEEE Trans Instrum Meas 71:5001614","journal-title":"IEEE Trans Instrum Meas"},{"key":"17948_CR32","doi-asserted-by":"crossref","first-page":"119157","DOI":"10.1016\/j.eswa.2022.119157","volume":"214","author":"R Fu","year":"2023","unstructured":"Fu R, Huang T, Li M, Sun Q, Chen Y (2023) A multimodal deep neural network for prediction of the driver\u2019s focus of attention based on anthropomorphic attention mechanism and prior knowledge. Expert Syst Appl 214:119157","journal-title":"Expert Syst Appl"},{"issue":"4","key":"17948_CR33","doi-asserted-by":"crossref","first-page":"2240008","DOI":"10.1142\/S0218213022400085","volume":"31","author":"L Zhang","year":"2022","unstructured":"Zhang L, Zhou Z, Ji P, Mei A (2022) Application of attention mechanism with prior information in natural language processing. Int J Artif Intell Tools 31(4):2240008","journal-title":"Int J Artif Intell Tools"},{"issue":"1","key":"17948_CR34","first-page":"586","volume":"14","author":"X Zheng","year":"2023","unstructured":"Zheng X, Gong W, Yang R, Zuo G (2023) Image segmentation of intestinal polyps using attention mechanism based on convolutional neural network. Int J Adv Comput Sci Appl 14(1):586\u2013593","journal-title":"Int J Adv Comput Sci Appl"},{"key":"17948_CR35","doi-asserted-by":"crossref","first-page":"106536","DOI":"10.1016\/j.asoc.2020.106536","volume":"96","author":"G Pang","year":"2020","unstructured":"Pang G, Wang X, Hao F, Wang L, Wang X (2020) Efficient point-of-interest recommendation with hierarchical attention mechanism. Appl Soft Comput 96:106536","journal-title":"Appl Soft Comput"},{"key":"17948_CR36","doi-asserted-by":"crossref","first-page":"1286","DOI":"10.1109\/ITAIC54216.2022.9836822","volume-title":"2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","author":"S Shen","year":"2022","unstructured":"Shen S, Jiang Y, Xu H (2022) A social recommendation model based on dual attention mechanism. 2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), vol 10. Chongqing, China, pp 1286\u20131290"},{"key":"17948_CR37","doi-asserted-by":"crossref","unstructured":"Li J, Wang Y, McAuley J (2020) Time interval aware self-attention for sequential recommendation. In: Proceedings of the 13th international conference on web search and data mining, Houston, TX, United states, pp 322\u2013330","DOI":"10.1145\/3336191.3371786"},{"key":"17948_CR38","doi-asserted-by":"crossref","first-page":"103753","DOI":"10.1016\/j.compind.2022.103753","volume":"143","author":"Y Liu","year":"2022","unstructured":"Liu Y, Gu F, Wu Y, Gu X, Guo J (2022) A metrics-based meta-learning model with meta-pretraining for industrial knowledge graph construction. Comput Ind 143:103753","journal-title":"Comput Ind"},{"key":"17948_CR39","first-page":"1","volume":"60","author":"J Li","year":"2022","unstructured":"Li J, Tian Y, Xu Y, Hu X, Zhang Z, Wang H, Xiao Y (2022) Mm-rcnn: toward few-shot object detection in remote sensing images with meta memory. IEEE Trans Geosci Remote Sens 60:1\u201314","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"17948_CR40","doi-asserted-by":"crossref","unstructured":"Neto AAF, Canuto AM (2014) Meta-learning and multi-objective optimization to design ensemble of classifiers. In: 2014 Brazilian conference on intelligent systems, pp 91\u201396","DOI":"10.1109\/BRACIS.2014.27"},{"issue":"3","key":"17948_CR41","doi-asserted-by":"crossref","first-page":"1048","DOI":"10.1109\/TCSVT.2021.3073410","volume":"32","author":"H Zhu","year":"2021","unstructured":"Zhu H, Li L, Wu J, Dong W, Shi G (2021) Generalizable no-reference image quality assessment via deep meta-learning. IEEE Trans Circuits Syst Video Technol 32(3):1048\u20131060","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"17948_CR42","doi-asserted-by":"crossref","unstructured":"Dong M, Yuan F, Yao L, Xu X, Zhu L (2020) Mamo: Memory-augmented meta-optimization for cold-start recommendation. In: Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining, pp 688\u2013697","DOI":"10.1145\/3394486.3403113"},{"issue":"9","key":"17948_CR43","doi-asserted-by":"crossref","first-page":"4385","DOI":"10.1109\/TKDE.2020.3039463","volume":"34","author":"Y Liu","year":"2022","unstructured":"Liu Y, Chen L, He X, Peng J, Zheng Z, Tang J (2022) Modelling high-order social relations for item recommendation. IEEE Trans Knowl Data Eng 34(9):4385\u20134397","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"2","key":"17948_CR44","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1109\/TKDE.2018.2833443","volume":"31","author":"C Shi","year":"2018","unstructured":"Shi C, Hu B, Zhao WX, Philip SY (2018) Heterogeneous information network embedding for recommendation. IEEE Trans Knowl Data Eng 31(2):357\u2013370","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"17948_CR45","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.ins.2019.09.007","volume":"510","author":"W Yuan","year":"2020","unstructured":"Yuan W, Wang H, Yu X, Liu N, Li Z (2020) Attention-based context-aware sequential recommendation model. Inf Sci 510:122\u2013134","journal-title":"Inf Sci"},{"issue":"2","key":"17948_CR46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3460198","volume":"40","author":"Y Cui","year":"2022","unstructured":"Cui Y, Sun H, Zhao Y, Yin H, Zheng K (2022) Sequential-knowledge-aware next POI recommendation: A meta-learning approach. ACM Trans Inf Syst (TOIS) 40(2):1\u201322","journal-title":"ACM Trans Inf Syst (TOIS)"},{"key":"17948_CR47","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.ins.2018.10.013","volume":"476","author":"X Chu","year":"2019","unstructured":"Chu X, Cai F, Cui C, Hu M, Li L, Qin Q (2019) Adaptive recommendation model using meta-learning for population-based algorithms. Inf Sci 476:192\u2013210","journal-title":"Inf Sci"},{"key":"17948_CR48","volume":"207","author":"H Lin","year":"2023","unstructured":"Lin H, Zhang S, Li Q, Li Y, Li J, Yang Y (2023) A new method for heart rate prediction based on LSTM-BiLSTM-Att. Measurement 207:112384","journal-title":"Measurement"},{"issue":"10","key":"17948_CR49","doi-asserted-by":"crossref","first-page":"3445","DOI":"10.1007\/s12555-021-0802-9","volume":"20","author":"J Ni","year":"2022","unstructured":"Ni J, Liu R, Tang G, Xie Y (2022) An improved attention-based bidirectional LSTM model for cyanobacterial bloom prediction. Int J Control Autom Syst 20(10):3445\u20133455","journal-title":"Int J Control Autom Syst"},{"key":"17948_CR50","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, UAI 2009, Montreal, Canada, pp 452\u2013461"},{"key":"17948_CR51","doi-asserted-by":"crossref","unstructured":"Kang W-C, McAuley J (2018) Self-attentive sequential recommendation. 2018 IEEE international conference on data mining (ICDM). Singapore, pp 197\u2013206","DOI":"10.1109\/ICDM.2018.00035"},{"key":"17948_CR52","first-page":"1073","volume-title":"25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2019","author":"H Lee","year":"2019","unstructured":"Lee H, Im J, Jang S, Cho H, Chung S (2019) Melu: Meta-learned user preference estimator for cold-start recommendation. 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2019. Anchorage, AK, United States, pp 1073\u20131082"},{"key":"17948_CR53","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1109\/ICDM50108.2020.00075","volume-title":"2020 IEEE International Conference on Data Mining (ICDM)","author":"T Wei","year":"2020","unstructured":"Wei T, Wu Z, Li R, Hu Z, Feng F, He X, Sun Y, Wang W (2020) Fast adaptation for cold-start collaborative filtering with meta-learning. 2020 IEEE International Conference on Data Mining (ICDM). Virtual, Sorrento, Italy, pp 661\u2013670"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17948-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17948-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17948-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,7]],"date-time":"2024-11-07T08:05:41Z","timestamp":1730966741000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17948-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,3]]},"references-count":53,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["17948"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17948-5","relation":{},"ISSN":["1573-7721"],"issn-type":[{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2024,1,3]]},"assertion":[{"value":"22 May 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 November 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 December 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 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 declared that they have no conflicts of interest to this work.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}]}}