{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T19:15:52Z","timestamp":1784142952781,"version":"3.55.0"},"reference-count":69,"publisher":"IGI Global Scientific Publishing","issue":"1","license":[{"start":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T00:00:00Z","timestamp":1731628800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T00:00:00Z","timestamp":1731628800000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T00:00:00Z","timestamp":1731628800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,15]]},"abstract":"<p>In multimodal sentiment analysis (MSA), the fusion strategies of multimodal features significantly influence the performance of MSA models. Previous works frequently face challenges in integrating heterogeneous data without fully leveraging the rich semantic content of text, resulting in poor information association. This paper propose an MSA model based on Text-Driven Crossmodal Fusion and Mutual Information Estimation, called TeD-MI, which comprises a Stacked Text-Driven Crossmodal Fusion (STDC) module, which efficiently fusions the three modalities driven by the text modality to optimize fusion feature representation and enhance semantic understanding. Furthermore, TeD-MI designed a mutual information estimation module to achieve the best balance between preserving task-related information and filtering out irrelevant noise information as much as possible. Comprehensive experiments conducted on the CMU-MOSI and CMU-MOSEI datasets demonstrate our proposed model achieves varying degrees of improvement across most evaluation metrics.<\/p>","DOI":"10.4018\/ijswis.359985","type":"journal-article","created":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T22:21:18Z","timestamp":1731709278000},"page":"1-27","source":"Crossref","is-referenced-by-count":4,"title":["Semantic-Driven Crossmodal Fusion for Multimodal Sentiment Analysis"],"prefix":"10.4018","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1569-4538","authenticated-orcid":true,"given":"Pingshan","family":"Liu","sequence":"first","affiliation":[{"name":"Guilin University of Electronic Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4663-279X","authenticated-orcid":true,"given":"Zhaoyang","family":"Wang","sequence":"additional","affiliation":[{"name":"Guilin University of Electronic Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fu","family":"Huang","sequence":"additional","affiliation":[{"name":"Guilin University of Electronic Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJSWIS.359985-0","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-016-3618-5"},{"key":"IJSWIS.359985-1"},{"key":"IJSWIS.359985-2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2909031"},{"key":"IJSWIS.359985-3","first-page":"32","article-title":"Learning representations by maximizing mutual information across views.","author":"P.Bachman","year":"2019","journal-title":"Advances in Neural Information Processing Systems"},{"key":"IJSWIS.359985-4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2798607"},{"key":"IJSWIS.359985-5","first-page":"531","article-title":"Mutual information neural estimation.","author":"M. I.Belghazi","year":"2018","journal-title":"International Conference on Machine Learning"},{"issue":"6","key":"IJSWIS.359985-6","first-page":"1150","article-title":"A survey on sentiment classification.","volume":"54","author":"L.Chen","year":"2017","journal-title":"Journal of Computer Research and Development"},{"key":"IJSWIS.359985-7","first-page":"1779","article-title":"Club: A contrastive log-ratio upper bound of mutual information.","author":"P.Cheng","year":"2020","journal-title":"International Conference on Machine Learning"},{"key":"IJSWIS.359985-8","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3048758"},{"key":"IJSWIS.359985-9","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853739"},{"key":"IJSWIS.359985-10","unstructured":"Diederik, P. K. (2014). Adam: A method for stochastic optimization."},{"key":"IJSWIS.359985-11","doi-asserted-by":"publisher","DOI":"10.1002\/cpa.3160360204"},{"key":"IJSWIS.359985-12","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2022.09.025"},{"key":"IJSWIS.359985-13","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.10.013"},{"key":"IJSWIS.359985-14"},{"key":"IJSWIS.359985-15","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413678"},{"key":"IJSWIS.359985-16","first-page":"770","article-title":"Deep residual learning for image recognition.","author":"K.He","year":"2016","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"IJSWIS.359985-17","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110502"},{"key":"IJSWIS.359985-18","first-page":"10944","article-title":"What makes multi-modal learning better than single (provably).","volume":"34","author":"Y.Huang","year":"2021","journal-title":"Advances in Neural Information Processing Systems"},{"key":"IJSWIS.359985-19","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2867718"},{"key":"IJSWIS.359985-20","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475692"},{"key":"IJSWIS.359985-21","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"key":"IJSWIS.359985-22","doi-asserted-by":"publisher","DOI":"10.4018\/IJSWIS.333865"},{"key":"IJSWIS.359985-23","first-page":"1513","article-title":"A variational information bottleneck approach to multi-omics data integration.","author":"C.Lee","year":"2021","journal-title":"International Conference on Artificial Intelligence and Statistics"},{"key":"IJSWIS.359985-24","doi-asserted-by":"publisher","DOI":"10.1093\/comjnl\/bxac153"},{"key":"IJSWIS.359985-25"},{"key":"IJSWIS.359985-26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1046"},{"key":"IJSWIS.359985-27","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2021.3068598"},{"key":"IJSWIS.359985-28","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3171679"},{"key":"IJSWIS.359985-29","doi-asserted-by":"publisher","DOI":"10.4018\/IJSSCI.300361"},{"key":"IJSWIS.359985-30","unstructured":"Ngiam, J., Khosla, A., Kim, M., Nam, J., Lee, H., & Ng, A. Y. (2011). Multimodal deep learning. In Proceedings of the 28th International Conference on MachineLearning (ICML-11), 689-696."},{"key":"IJSWIS.359985-31","first-page":"1089","article-title":"Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization.","volume":"20","author":"X.Nguyen","year":"2007","journal-title":"Advances in Neural Information Processing Systems"},{"key":"IJSWIS.359985-32","first-page":"29","article-title":"F-gan: Training generative neural samplers using variational divergence minimization.","author":"S.Nowozin","year":"2016","journal-title":"Advances in Neural Information Processing Systems"},{"key":"IJSWIS.359985-33","doi-asserted-by":"crossref","unstructured":"Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends\u00ae in Information Retrieval, 2(1\u20132), 1-135.","DOI":"10.1561\/1500000011"},{"key":"IJSWIS.359985-34","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"IJSWIS.359985-35","doi-asserted-by":"publisher","DOI":"10.1511\/2001.28.344"},{"key":"IJSWIS.359985-36","first-page":"5171","article-title":"On variational bounds of mutual information.","author":"B.Poole","year":"2019","journal-title":"International Conference on Machine Learning"},{"key":"IJSWIS.359985-37","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.134"},{"key":"IJSWIS.359985-38","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3157712"},{"key":"IJSWIS.359985-39","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.214"},{"key":"IJSWIS.359985-40","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3009482"},{"key":"IJSWIS.359985-41","doi-asserted-by":"publisher","DOI":"10.1088\/1742-5468\/ab3985"},{"key":"IJSWIS.359985-42","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"IJSWIS.359985-43","doi-asserted-by":"publisher","DOI":"10.4018\/IJSWIS.2021040104"},{"key":"IJSWIS.359985-44","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2017.08.003"},{"key":"IJSWIS.359985-45","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106755"},{"key":"IJSWIS.359985-46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i05.6431"},{"key":"IJSWIS.359985-47","doi-asserted-by":"publisher","DOI":"10.1109\/ITW.2015.7133169"},{"key":"IJSWIS.359985-48","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3160060"},{"key":"IJSWIS.359985-49","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1656"},{"key":"IJSWIS.359985-50"},{"key":"IJSWIS.359985-51"},{"key":"IJSWIS.359985-52","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.109259"},{"key":"IJSWIS.359985-53","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380000"},{"key":"IJSWIS.359985-54","doi-asserted-by":"publisher","DOI":"10.1145\/3462244.3479931"},{"key":"IJSWIS.359985-55","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107676"},{"key":"IJSWIS.359985-56","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.417"},{"key":"IJSWIS.359985-57","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413690"},{"key":"IJSWIS.359985-58","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.343"},{"key":"IJSWIS.359985-59","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17289"},{"key":"IJSWIS.359985-60"},{"key":"IJSWIS.359985-61","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12021"},{"key":"IJSWIS.359985-62","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12021"},{"key":"IJSWIS.359985-63","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12024"},{"key":"IJSWIS.359985-64","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2016.94"},{"key":"IJSWIS.359985-65","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1208"},{"key":"IJSWIS.359985-66","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2022.07.006"},{"key":"IJSWIS.359985-67","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2021.3096037"},{"key":"IJSWIS.359985-68","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.02.028"}],"container-title":["International Journal on Semantic Web and Information Systems"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=359985","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,5]],"date-time":"2025-02-05T06:33:24Z","timestamp":1738737204000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJSWIS.359985"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2024,11,15]]},"references-count":69,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1]]}},"URL":"https:\/\/doi.org\/10.4018\/ijswis.359985","relation":{},"ISSN":["1552-6283","1552-6291"],"issn-type":[{"value":"1552-6283","type":"print"},{"value":"1552-6291","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,15]]}}}