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Syst."],"published-print":{"date-parts":[[2025,5,31]]},"abstract":"<jats:p>\n            Personalized micro video recommendation aims to recommend the micro videos tailored to user preference based on the user\u2019s interaction history with the micro videos, which has drawn increasing attention from both the academic and industrial communities. Existing solutions primarily concentrate on video-level interactions between users and micro videos to model their preferences, and cannot distinguish the finer-grained users\u2019 interactions with various modalities. Ignoring modality-level interactions prevents the full understanding of the user\u2019s true and subtle preferences on micro videos. To this end, in this article, we propose a Contrastive Multimodal Interaction Graph Learning (\n            <jats:italic>MVideoRec<\/jats:italic>\n            ) model to automatically and explicitly learn the modality-level interaction between users and micro videos for recommendations. Specifically, we designed a graph structure learning module with a sparsification strategy to infer modality-level interaction graph, which will be dynamically and iteratively updated based on the node representations obtained from the node representation learning module. Furthermore, to address the lack of ground truth labels, we propose to generate teacher view from video-level interaction graph and student view from modality-level interaction graph, as well as construct intra-modality and inter-modality contrastive pairwise instances to provide self-supervised signals. Extensive experiments on three real-world micro video datasets validate the effectiveness of MVideoRec.\n          <\/jats:p>","DOI":"10.1145\/3711855","type":"journal-article","created":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T14:31:36Z","timestamp":1737729096000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["MVideoRec: Micro Video Recommendations through Modality Decomposition and Contrastive Learning"],"prefix":"10.1145","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8503-2535","authenticated-orcid":false,"given":"Li","family":"Yu","sequence":"first","affiliation":[{"name":"School of Information, Renmin University of China, Beijing, China and Suzhou Key Laboratory of Artificial Intelligence and Social Governance Technology, Suzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1014-7397","authenticated-orcid":false,"given":"Jianyong","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Information, Renmin University of China, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8607-6246","authenticated-orcid":false,"given":"Qihan","family":"Du","sequence":"additional","affiliation":[{"name":"School of Information, Renmin University of China, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5418-6969","authenticated-orcid":false,"given":"Xi","family":"Niu","sequence":"additional","affiliation":[{"name":"College of Computing and Informatics, The University of North Carolina at Charlotte, Charlotte, NC, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,2,26]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3617827"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3617826"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.9973"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.05.022"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080797"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313513"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548420"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3059508"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548399"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2020.102277"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351034"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532027"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/S11042-017-4827-2"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413556"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411947"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3138298"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICME52920.2022.9859663"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747580"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP43922.2022.9747757"},{"key":"e_1_3_3_22_2","unstructured":"Thomas N. 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