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To this end, we introduce the unified heterogeneous Hypergraph construction for the Incomplete multimedia REcommendation (\n            <jats:monospace>HIRE<\/jats:monospace>\n            ), a novel framework designed to jointly learn a heterogeneous hypergraph and perform accurate recommendations under incomplete scenarios.\n            <jats:monospace>HIRE<\/jats:monospace>\n            first initializes the unified heterogeneous hypergraph for modality completion and employs self-supervised learning aligned with the contrastive text-centered view for multimedia recommendation. Such integration effectively handles the challenges posed by incomplete modalities, leading to improved recommendation accuracy. Furthermore, we find that the hypergraph directly learned from the\n            <jats:monospace>HIRE<\/jats:monospace>\n            is a dense structure which can be inaccurate and coarse. Therefore, we devise the\n            <jats:monospace>HIRE<\/jats:monospace>\n            framework with Sparse constraint named\n            <jats:monospace>HIRES<\/jats:monospace>\n            , which uniquely integrates optimal transport and a\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\(\\ell_{2,1}\\)<\/jats:tex-math>\n            <\/jats:inline-formula>\n            -norm to refine the hypergraph structure. Our extensive experiments across various datasets demonstrate the superiority of\n            <jats:monospace>HIRES<\/jats:monospace>\n            in addressing incomplete modalities, establishing it as a powerful tool for personalized multimedia recommendations.\n          <\/jats:p>","DOI":"10.1145\/3745020","type":"journal-article","created":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T10:48:57Z","timestamp":1750762137000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Unified Heterogeneous Hypergraph Construction for Incomplete Multimedia Recommendation"],"prefix":"10.1145","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7495-3846","authenticated-orcid":false,"given":"Zhenghong","family":"Lin","sequence":"first","affiliation":[{"name":"Fuzhou University, Fuzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3526-6859","authenticated-orcid":false,"given":"Yanchao","family":"Tan","sequence":"additional","affiliation":[{"name":"Fuzhou University, Fuzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4284-8080","authenticated-orcid":false,"given":"Jiamin","family":"Chen","sequence":"additional","affiliation":[{"name":"Fuzhou University, Fuzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8100-2787","authenticated-orcid":false,"given":"Hengyu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Macquarie University, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1419-964X","authenticated-orcid":false,"given":"Chaochao","family":"Chen","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5195-9682","authenticated-orcid":false,"given":"Shiping","family":"Wang","sequence":"additional","affiliation":[{"name":"Fuzhou University, Fuzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9145-4531","authenticated-orcid":false,"given":"Carl","family":"Yang","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,8,8]]},"reference":[{"key":"e_1_3_1_2_2","first-page":"677","volume-title":"Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR \u201924)","author":"Bai H.","year":"2024","unstructured":"H. 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