{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T21:23:40Z","timestamp":1783027420130,"version":"3.54.6"},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T00:00:00Z","timestamp":1782950400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T00:00:00Z","timestamp":1782950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62377023"],"award-info":[{"award-number":["62377023"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Key Project of Hubei Provincial Natural Science Foundation Innovation and Development Joint Found","award":["2025AFD195"],"award-info":[{"award-number":["2025AFD195"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"DOI":"10.1007\/s11227-026-08685-1","type":"journal-article","created":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T19:30:52Z","timestamp":1783020652000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Improved evidence theory based on information fusion for multimodal emotion recognition"],"prefix":"10.1007","volume":"82","author":[{"given":"Kejiang","family":"Xiao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenqi","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guangjie","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiefan","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiyan","family":"Pang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chongming","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,2]]},"reference":[{"key":"8685_CR1","doi-asserted-by":"publisher","first-page":"8316","DOI":"10.1109\/TIP.2020.3011846","volume":"29","author":"N Perveen","year":"2020","unstructured":"Perveen N, Roy D, Chalavadi KM (2020) Facial expression recognition in videos using dynamic kernels. IEEE Trans Image Process 29:8316\u20138325","journal-title":"IEEE Trans Image Process"},{"key":"8685_CR2","doi-asserted-by":"publisher","first-page":"2697","DOI":"10.1109\/TASLP.2020.3023632","volume":"28","author":"S Parthasarathy","year":"2020","unstructured":"Parthasarathy S, Busso C (2020) Semi-supervised speech emotion recognition with ladder networks. IEEE\/ACM Trans Audio Speech and Lang Proc 28:2697\u20132709","journal-title":"IEEE\/ACM Trans Audio Speech and Lang Proc"},{"issue":"10","key":"8685_CR3","doi-asserted-by":"publisher","first-page":"3030","DOI":"10.1109\/TCSVT.2017.2719043","volume":"28","author":"S Zhang","year":"2018","unstructured":"Zhang S, Zhang S, Huang T, Gao W, Tian Q (2018) Learning affective features with a hybrid deep model for audio\u2013visual emotion recognition. IEEE Trans Circuits Syst Video Technol 28(10):3030\u20133043","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"issue":"1","key":"8685_CR4","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1109\/TAFFC.2021.3053275","volume":"14","author":"J Deng","year":"2023","unstructured":"Deng J, Ren F (2023) A survey of textual emotion recognition and its challenges. IEEE Trans Affect Comput 14(1):49\u201367","journal-title":"IEEE Trans Affect Comput"},{"key":"8685_CR5","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.ins.2022.12.014","volume":"623","author":"Y Dai","year":"2023","unstructured":"Dai Y, Yan Z, Cheng J, Duan X, Wang G (2023) Analysis of multimodal data fusion from an information theory perspective. Inf Sci 623:164\u2013183","journal-title":"Inf Sci"},{"key":"8685_CR6","doi-asserted-by":"crossref","unstructured":"Liu S, Zhao H, Chen Y, Kong F, Li K (2025) Cu-semlp: All-mlp-based multimodal interaction model for multimodal sentiment analysis. J Supercomput 81","DOI":"10.1007\/s11227-025-07364-x"},{"key":"8685_CR7","doi-asserted-by":"crossref","unstructured":"Wei Y, Chen J (2025) An efficient utterance-level context-aware fusion architecture for large-scale audio-text sentiment analysis. J Supercomput 81","DOI":"10.1007\/s11227-025-07930-3"},{"issue":"2","key":"8685_CR8","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1214\/aoms\/1177698950","volume":"38","author":"AP Dempster","year":"1967","unstructured":"Dempster AP (1967) Upper and lower probabilities induced by a multivalued mapping. Ann Math Stat 38(2):325\u2013339","journal-title":"Ann Math Stat"},{"issue":"1","key":"8685_CR9","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1080\/00401706.1978.10489628","volume":"20","author":"GA Shafer","year":"1978","unstructured":"Shafer GA (1978) A mathematical theory of evidence. Technometrics 20(1):106\u2013106","journal-title":"Technometrics"},{"issue":"06","key":"8685_CR10","first-page":"1092","volume":"40","author":"B Kang","year":"2012","unstructured":"Kang B, Li Y, Deng Y (2012) Basic probability assignment generation method based on interval numbers and its application. J Electron 40(06):1092\u20131096","journal-title":"J Electron"},{"key":"8685_CR11","doi-asserted-by":"crossref","unstructured":"Zhong S, Liu X (2019) A new method to determine basic probability assignment based on interval number. In: 2019 Computing, Communications and IoT Applications (ComComAp), p. 316\u2013320","DOI":"10.1109\/ComComAp46287.2019.9018805"},{"key":"8685_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119150","volume":"642","author":"R Kavya","year":"2023","unstructured":"Kavya R, Jabez C, Subhrakanta P (2023) A new belief interval-based total uncertainty measure for Dempster\u2013Shafer theory. Inf Sci 642:119150","journal-title":"Inf Sci"},{"key":"8685_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.102113","volume":"103","author":"Z Shao","year":"2024","unstructured":"Shao Z, Dou W, Pan Y (2024) Dual-level deep evidential fusion: integrating multimodal information for enhanced reliable decision-making in deep learning. Inf Fusion 103:102113","journal-title":"Inf Fusion"},{"key":"8685_CR14","doi-asserted-by":"crossref","unstructured":"Fu Y, Tang Y, Zhou D (2022) A new generation method of basic probability assignment based on the normal membership function. In: 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), p. 385\u2013390","DOI":"10.1109\/SMC53654.2022.9945225"},{"key":"8685_CR15","first-page":"1","volume":"73","author":"K Zhou","year":"2024","unstructured":"Zhou K, Lu N, Jiang B (2024) Basic probability assignment using intuitive fuzzy cloud model for information fusion and its application in fault diagnosis. IEEE Trans Instrum Meas 73:1\u201313","journal-title":"IEEE Trans Instrum Meas"},{"key":"8685_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105512","volume":"85","author":"W Ma","year":"2019","unstructured":"Ma W, Jiang Y, Luo X (2019) A flexible rule for evidential combination in Dempster\u2013Shafer theory of evidence. Appl Soft Comput 85:105512","journal-title":"Appl Soft Comput"},{"key":"8685_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.inffus.2023.01.009","volume":"94","author":"X Liu","year":"2023","unstructured":"Liu X, Liu S, Xiang J, Sun R (2023) A conflict evidence fusion method based on the composite discount factor and the game theory. Inf Fusion 94:1\u201316","journal-title":"Inf Fusion"},{"key":"8685_CR18","doi-asserted-by":"crossref","unstructured":"Jousselme A-L, Grenier D, Boss\u00e9, (2001) A new distance between two bodies of evidence. Inf Fusion 2(2):91\u2013101","DOI":"10.1016\/S1566-2535(01)00026-4"},{"key":"8685_CR19","doi-asserted-by":"crossref","unstructured":"Zhang X, Tang Y, Zhou D (2022) A novel conflict measurement method based on cosine similarity and deng entropy in Dempster\u2013Shafer evidence theory. In: 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), p. 3198\u20133203","DOI":"10.1109\/SMC53654.2022.9945121"},{"issue":"8","key":"8685_CR20","doi-asserted-by":"publisher","first-page":"7609","DOI":"10.1109\/TKDE.2022.3206871","volume":"35","author":"F Xiao","year":"2023","unstructured":"Xiao F, Cao Z, Lin C-T (2023) A complex weighted discounting multisource information fusion with its application in pattern classification. IEEE Trans Knowl Data Eng 35(8):7609\u20137623","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"8685_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2025.110351","volume":"148","author":"J Lin","year":"2025","unstructured":"Lin J, Xie K (2025) A weighted graph network-based method for combining conflicting evidence. Eng Appl Artif Intell 148:110351","journal-title":"Eng Appl Artif Intell"},{"issue":"1","key":"8685_CR22","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1109\/TKDE.2020.2982393","volume":"34","author":"C Ye","year":"2022","unstructured":"Ye C, Wang H, Zheng K, Kong Y, Zhu R, Gao J, Li J (2022) Constrained truth discovery. IEEE Trans Knowl Data Eng 34(1):205\u2013218","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"3","key":"8685_CR23","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1109\/TKDE.2018.2837026","volume":"31","author":"H Xiao","year":"2019","unstructured":"Xiao H, Gao J, Li Q, Ma F, Su L, Feng Y, Zhang A (2019) Towards confidence interval estimation in truth discovery. IEEE Trans Knowl Data Eng 31(3):575\u2013588","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"6","key":"8685_CR24","first-page":"5521","volume":"35","author":"H Xiao","year":"2023","unstructured":"Xiao H, Wang S (2023) A joint maximum likelihood estimation framework for truth discovery: a unified perspective. IEEE Trans Knowl Data Eng 35(6):5521\u20135533","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"7","key":"8685_CR25","first-page":"6941","volume":"35","author":"F Xiao","year":"2023","unstructured":"Xiao F, Wen J, Pedrycz W (2023) Generalized divergence-based decision making method with an application to pattern classification. IEEE Trans Knowl Data Eng 35(7):6941\u20136956","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"4","key":"8685_CR26","doi-asserted-by":"publisher","first-page":"2246","DOI":"10.1109\/TSMC.2022.3211498","volume":"53","author":"F Xiao","year":"2023","unstructured":"Xiao F (2023) Gejs: a generalized evidential divergence measure for multisource information fusion. IEEE Trans Syst Man Cybern Syst 53(4):2246\u20132258","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"8685_CR27","doi-asserted-by":"crossref","unstructured":"Yu N, Yang K, Gan M (2022) Research on the improved method of d-s evidence theory based on the fusion of support and confidence entropy. In: 2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ), p. 1610\u20131615","DOI":"10.1109\/IAEAC54830.2022.9929927"},{"issue":"7","key":"8685_CR28","first-page":"6811","volume":"35","author":"D-V Vo","year":"2023","unstructured":"Vo D-V, Tran T-T, Shirai K, Huynh V-N (2023) Deep generative networks coupled with evidential reasoning for dynamic user preferences using short texts. IEEE Trans Knowl Data Eng 35(7):6811\u20136826","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"8685_CR29","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.inffus.2020.12.004","volume":"70","author":"D-V Vo","year":"2021","unstructured":"Vo D-V, Karnjana J, Huynh V-N (2021) An integrated framework of learning and evidential reasoning for user profiling using short texts. Inf Fusion 70:27\u201342","journal-title":"Inf Fusion"},{"issue":"9","key":"8685_CR30","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1007\/s40747-025-01999-2","volume":"11","author":"Z Qiu","year":"2025","unstructured":"Qiu Z, Qin Y, Chen Z, Zeng L, Cai R (2025) Overcoming negative weighting in uncertainty-based methods: a multi-uncertainty clustering method for evidence fusion. Complex Intell Syst 11(9):383","journal-title":"Complex Intell Syst"},{"issue":"4","key":"8685_CR31","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1007\/s44443-025-00084-5","volume":"37","author":"Y Qin","year":"2025","unstructured":"Qin Y, Zhang J, Qiu Z, Chen Z, Cai R (2025) Boosting complex evidence theory with complex belief Renyi divergence for multi-source information fusion. J King Saud Univ Comput Inf Sci 37(4):66","journal-title":"J King Saud Univ Comput Inf Sci"},{"key":"8685_CR32","doi-asserted-by":"crossref","unstructured":"Zhao A, Li J, Liu H (2022) Determination of basic probability assignment based on membership function and pca. In: 2022 7th International Conference on Robotics and Automation Engineering (ICRAE), p. 401\u2013405","DOI":"10.1109\/ICRAE56463.2022.10056187"},{"issue":"2","key":"8685_CR33","doi-asserted-by":"publisher","first-page":"1595","DOI":"10.1007\/s13369-021-06011-w","volume":"47","author":"S Wang","year":"2022","unstructured":"Wang S, Tang Y (2022) An improved approach for generation of a basic probability assignment in the evidence theory based on Gaussian-BPAGaussian distribution. Arab J Sci Eng 47(2):1595\u20131607","journal-title":"Arab J Sci Eng"},{"issue":"7","key":"8685_CR34","first-page":"1477","volume":"28","author":"F Xiao","year":"2020","unstructured":"Xiao F (2020) Efmcdm: evidential fuzzy multicriteria decision making based on belief entropy. IEEE Trans Fuzzy Syst 28(7):1477\u20131491","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"8685_CR35","doi-asserted-by":"crossref","unstructured":"Mao K, Wang Y, Zhou W, Ye J, Fang B (2025) Evaluation of belief entropies from the perspective of evidential neural network 58(5):133","DOI":"10.1007\/s10462-025-11130-z"},{"key":"8685_CR36","unstructured":"Huang Y, Du C, Xue Z, Chen X, Zhao H, Huang L (2021) What makes multi-modal learning better than single (provably). In: Proceedings of the 35th International Conference on Neural Information Processing Systems. NIPS \u201921. Curran Associates Inc., Red Hook, NY, USA"},{"key":"8685_CR37","doi-asserted-by":"crossref","unstructured":"Zadeh A, Chen M, Poria S, Cambria E, Morency L-P (2017) Tensor fusion network for multimodal sentiment analysis. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Copenhagen, Denmark, p. 1103\u20131114","DOI":"10.18653\/v1\/D17-1115"},{"key":"8685_CR38","doi-asserted-by":"crossref","unstructured":"Williams J, Kleinegesse S, Comanescu R, Radu O (2018) Recognizing emotions in video using multimodal DNN feature fusion. In: Zadeh A, Liang PP, Morency L-P, Poria S, Cambria E, Scherer S (eds.) Proceedings of Grand Challenge and Workshop on Human Multimodal Language (Challenge-HML), Melbourne, Australia, p. 11\u201319","DOI":"10.18653\/v1\/W18-3302"},{"key":"8685_CR39","doi-asserted-by":"crossref","unstructured":"Tsai Y-HH, Bai S, Liang PP, Kolter JZ, Morency L-P, Salakhutdinov R (2019) Multimodal transformer for unaligned multimodal language sequences. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics, Florence, Italy, p. 6558\u20136569","DOI":"10.18653\/v1\/P19-1656"},{"key":"8685_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109259","volume":"136","author":"D Wang","year":"2023","unstructured":"Wang D, Guo X, Tian Y, Liu J, He L, Luo X (2023) Tetfn: a text enhanced transformer fusion network for multimodal sentiment analysis. Pattern Recogn 136:109259","journal-title":"Pattern Recogn"},{"key":"8685_CR41","doi-asserted-by":"crossref","unstructured":"Zadeh A, Liang PP, Mazumder N, Poria S, Cambria E, Morency L-P (2018) Memory fusion network for multi-view sequential learning. Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence. AAAI Press, New Orleans, Louisiana, USA, p 32","DOI":"10.1609\/aaai.v32i1.12021"},{"key":"8685_CR42","doi-asserted-by":"crossref","unstructured":"Hazarika D, Zimmermann R, Poria S (2020) Misa: Modality-invariant and -specific representations for multimodal sentiment analysis. In: Proceedings of the 28th ACM International Conference on Multimedia. MM \u201920, Association for Computing Machinery, New York, NY, USA, p. 1122\u20131131","DOI":"10.1145\/3394171.3413678"},{"key":"8685_CR43","first-page":"10790","volume":"35","author":"W Yu","year":"2021","unstructured":"Yu W, Xu H, Yuan Z, Wu J (2021) Learning modality-specific representations with self-supervised multi-task learning for multimodal sentiment analysis. Proc AAAI Conf Artif Intell 35:10790\u201310797","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"8685_CR44","unstructured":"Simonyan K, Zisserman A (2014) Two-stream convolutional networks for action recognition in videos. In: Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 1. NIPS\u201914, MIT Press, Cambridge, MA, USA, p. 568\u2013576"},{"key":"8685_CR45","doi-asserted-by":"crossref","unstructured":"Tsanousa A, Meditskos G, Vrochidis S, Kompatsiaris I (2019) A weighted late fusion framework for recognizing human activity from wearable sensors. 2019 10th International Conference on Information. Intelligence, Systems and Applications (IISA), pp 1\u20138","DOI":"10.1109\/IISA.2019.8900725"},{"key":"8685_CR46","doi-asserted-by":"crossref","unstructured":"Morvant E, Habrard A, Ayache S (2014) Majority vote of diverse classifiers for late fusion. In: Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition - Volume 8621. S+SSPR 2014, Springer, Berlin, Heidelberg, p. 153\u2013162","DOI":"10.1007\/978-3-662-44415-3_16"},{"issue":"2","key":"8685_CR47","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1109\/91.227387","volume":"1","author":"R Krishnapuram","year":"1993","unstructured":"Krishnapuram R, Keller JM (1993) A possibilistic approach to clustering. IEEE Trans Fuzzy Syst 1(2):98\u2013110","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"1","key":"8685_CR48","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1016\/S0377-0427(00)00342-3","volume":"121","author":"G Alefeld","year":"2000","unstructured":"Alefeld G, Mayer G (2000) Interval analysis: theory and applications. J Comput Appl Math 121(1):421\u2013464","journal-title":"J Comput Appl Math"},{"key":"8685_CR49","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K (2019) BERT: Pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Association for Computational Linguistics, Minneapolis, Minnesota, p. 4171\u20134186"},{"key":"8685_CR50","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017) Attention is all you need. In: Proceedings of the 31st International Conference on Neural Information Processing Systems. NIPS\u201917, Curran Associates Inc., Red Hook, NY, USA, p. 6000\u20136010"},{"key":"8685_CR51","doi-asserted-by":"crossref","unstructured":"Degottex G, Kane J, Drugman T, Raitio T, Scherer S (2014) Covarep \u2014 a collaborative voice analysis repository for speech technologies. In: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), p. 960\u2013964","DOI":"10.1109\/ICASSP.2014.6853739"},{"issue":"10","key":"8685_CR52","doi-asserted-by":"publisher","first-page":"1499","DOI":"10.1109\/LSP.2016.2603342","volume":"23","author":"K Zhang","year":"2016","unstructured":"Zhang K, Zhang Z, Li Z, Qiao Y (2016) Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Process Lett 23(10):1499\u20131503","journal-title":"IEEE Signal Process Lett"},{"key":"8685_CR53","doi-asserted-by":"crossref","unstructured":"Baltrusaitis T, Zadeh A, Lim YC, Morency LP (2018) Openface 2.0: Facial behavior analysis toolkit. IEEE Computer Society, pp 59\u201366","DOI":"10.1109\/FG.2018.00019"},{"key":"8685_CR54","unstructured":"Huang Z, Xu W, Yu K (2015) Bidirectional lstm-crf models for sequence tagging. Computer Science"},{"key":"8685_CR55","unstructured":"Zadeh A, Zellers R, Morency PE, L-P (2016) Mosi: Multimodal corpus of sentiment intensity and subjectivity analysis in online opinion videos. arXiv Computation and Language"},{"key":"8685_CR56","doi-asserted-by":"crossref","unstructured":"Bagher\u00a0Zadeh A, Liang PP, Poria S, Cambria E, Morency L-P (2018) Multimodal language analysis in the wild: CMU-MOSEI dataset and interpretable dynamic fusion graph. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Association for Computational Linguistics, Melbourne, Australia, pp. 2236\u20132246","DOI":"10.18653\/v1\/P18-1208"},{"key":"8685_CR57","doi-asserted-by":"crossref","unstructured":"Dai W, Cahyawijaya S, Liu Z, Fung P (2021) Multimodal end-to-end sparse model for emotion recognition. In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Association for Computational Linguistics, Online, p. 5305\u20135316","DOI":"10.18653\/v1\/2021.naacl-main.417"},{"issue":"3","key":"8685_CR58","doi-asserted-by":"publisher","first-page":"2209","DOI":"10.1109\/TAFFC.2022.3178231","volume":"14","author":"Y Sun","year":"2023","unstructured":"Sun Y, Mai S, Hu H (2023) Learning to learn better unimodal representations via adaptive multimodal meta-learning. IEEE Trans Affect Comput 14(3):2209\u20132223","journal-title":"IEEE Trans Affect Comput"},{"key":"8685_CR59","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1007\/978-3-319-77116-8_13","volume-title":"Computational linguistics and intelligent text processing","author":"E Cambria","year":"2018","unstructured":"Cambria E, Hazarika D, Poria S, Hussain A, Subramanyam RBV (2018) Benchmarking multimodal sentiment analysis. In: Gelbukh A (ed) Computational linguistics and intelligent text processing. Springer, Cham, pp 166\u2013179"},{"key":"8685_CR60","doi-asserted-by":"crossref","unstructured":"Liu Z, Shen Y, Lakshminarasimhan VB, Liang PP, Bagher\u00a0Zadeh A, Morency L-P (2018) Efficient low-rank multimodal fusion with modality-specific factors. In: Gurevych I, Miyao Y (eds.) Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Association for Computational Linguistics, Melbourne, Australia, p. 2247\u20132256","DOI":"10.18653\/v1\/P18-1209"},{"key":"8685_CR61","doi-asserted-by":"publisher","first-page":"4909","DOI":"10.1109\/TMM.2022.3183830","volume":"25","author":"D Wang","year":"2023","unstructured":"Wang D, Liu S, Wang Q, Tian Y, He L, Gao X (2023) Cross-modal enhancement network for multimodal sentiment analysis. IEEE Trans Multimed 25:4909\u20134921","journal-title":"IEEE Trans Multimed"},{"key":"8685_CR62","doi-asserted-by":"publisher","first-page":"333","DOI":"10.15837\/ijccc.2015.3.1656","volume":"10","author":"W Jiang","year":"2015","unstructured":"Jiang W, Yang Y, Luo Y-Y, Qin X-Y (2015) Determining basic probability assignment based on the improved similarity measures of generalized fuzzy numbers. Int J Comput Commun Control 10:333\u2013347","journal-title":"Int J Comput Commun Control"},{"issue":"2","key":"8685_CR63","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/0020-0255(87)90007-7","volume":"41","author":"RR Yager","year":"1987","unstructured":"Yager RR (1987) On the Dempster\u2013Shafer framework and new combination rules. Inf Sci 41(2):93\u2013137","journal-title":"Inf Sci"},{"issue":"1","key":"8685_CR64","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0167-9236(99)00084-6","volume":"29","author":"CK Murphy","year":"2000","unstructured":"Murphy CK (2000) Combining belief functions when evidence conflicts. Decis Support Syst 29(1):1\u20139","journal-title":"Decis Support Syst"},{"key":"8685_CR65","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1016\/j.chaos.2016.07.014","volume":"91","author":"Y Deng","year":"2016","unstructured":"Deng Y (2016) Deng entropy. Chaos Solitons & Fractals 91:549\u2013553","journal-title":"Chaos Solitons & Fractals"},{"key":"8685_CR66","first-page":"117","volume":"08","author":"Q Sun","year":"2000","unstructured":"Sun Q, Ye X, Gu W (2000) A new synthetic formula based on evidence theory. J Electron 08:117\u2013119","journal-title":"J Electron"},{"issue":"06","key":"8685_CR67","first-page":"141","volume":"37","author":"L Xue","year":"2013","unstructured":"Xue L, Kang J (2013) Improved d-s evidence theory algorithm. Inf Technol 37(06):141\u2013144","journal-title":"Inf Technol"},{"issue":"19","key":"8685_CR68","first-page":"96","volume":"42","author":"P Lv","year":"2019","unstructured":"Lv P, Shi J, Qin Y (2019) A d-s improved algorithm for resolving evidence conflicts. Electron Meas Technol 42(19):96\u2013100","journal-title":"Electron Meas Technol"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-026-08685-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-026-08685-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-026-08685-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T21:01:27Z","timestamp":1783026087000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-026-08685-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,2]]},"references-count":68,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["8685"],"URL":"https:\/\/doi.org\/10.1007\/s11227-026-08685-1","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,2]]},"assertion":[{"value":"11 October 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"546"}}