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Intell. Syst. Technol."],"published-print":{"date-parts":[[2026,2,28]]},"abstract":"<jats:p>Unfair recommendations stem from user-sensitive attributes and information transmission biases. Graph-structured data can provide more balanced information for fair recommendations by capturing multidimensional user\u2013item interactions. However, graph-based fair recommendation still faces some challenges: Traditional graphs rely on static edge-connected topology, struggling to dynamically update many-to-many relationships, which impairs the long-term fairness modeling; Most existing graph mining algorithms overlook individual differences arising from filtered sensitive information, thereby exacerbating the fairness-accuracy tradeoff; Hypergraph neural networks\u2019 propagation relies on structural density, while sparse connections reduce it, leading to inaccurate representations in sparse regions and uneven diffusion. To address these issues, we propose a structure-aware fair recommendation approach based on counterfactual dynamic hypergraphs (FairCH). First, we propose a multidimensional user fairness model that captures many-to-many higher-order user\u2013item relationships and their preference-fairness co-evolution via dynamic hypergraphs. Second, sensitive information is filtered through adversarial learning, and counterfactual hyperedges is reconstructed by counterfactual reasoning, compensating for information loss. Finally, a cross-hierarchy structure-aware model is proposed, which extracts counterfactual fairness layers, global preference layers, and shared evolution layers from hypergraphs and integrates them via an inter-layer interactive attention mechanism to enhance information propagation and mitigate structural biases. Experimental results demonstrate that FairCH exhibits superior recommendation performance to the baselines.<\/jats:p>","DOI":"10.1145\/3773913","type":"journal-article","created":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T16:03:20Z","timestamp":1761667400000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Structure-Aware Fair Recommendation Approach Based on Counterfactual Dynamic Hypergraphs"],"prefix":"10.1145","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3421-4387","authenticated-orcid":false,"given":"Shanshan","family":"Wan","sequence":"first","affiliation":[{"name":"School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2570-7051","authenticated-orcid":false,"given":"Zebin","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2187-0830","authenticated-orcid":false,"given":"Qiyi","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0352-3002","authenticated-orcid":false,"given":"Chuyuan","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing, China and Beijing Key Laboratory of Super Intelligent Technology for Urban Architecture, Beijing University of Civil Engineering and Architecture, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5972-559X","authenticated-orcid":false,"given":"Chang-Dong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,12,19]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1905.10674"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3638352"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441752"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-024-1510-8"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3640457.3688113"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512173"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3265598"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/2090236.2090255"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313488"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1111\/ajps.12649"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3639048"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1610.02413"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403253"},{"key":"e_1_3_2_16_2","unstructured":"Diederik P. 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