{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T01:20:17Z","timestamp":1779326417245,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,12,14]]},"DOI":"10.1145\/3719384.3719440","type":"proceedings-article","created":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T14:44:03Z","timestamp":1752072243000},"page":"379-385","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Multi-modal clothing recommendation model based on large model andVAEenhancement"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-0481-1021","authenticated-orcid":false,"given":"Bingjie","family":"Huang","sequence":"first","affiliation":[{"name":"Independent researcher, USA, Sunnyvale, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6857-981X","authenticated-orcid":false,"given":"Qingyi","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Brown University, USA, RI, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6384-5867","authenticated-orcid":false,"given":"Shuaishuai","family":"Huang","sequence":"additional","affiliation":[{"name":"Independent researcher, China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8894-2937","authenticated-orcid":false,"given":"Xue-She","family":"Wang","sequence":"additional","affiliation":[{"name":"Pratt School of Engineering, Duke University, USA, Durham, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3948-3061","authenticated-orcid":false,"given":"Haowei","family":"Yang","sequence":"additional","affiliation":[{"name":"Cullen College of Engineering, University of Houston, USA, Houston, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,7,9]]},"reference":[{"key":"e_1_3_3_1_1_2","series-title":"Vol. 1","volume-title":"Recommender systems","author":"C.","year":"2016","unstructured":"Aggarwal, C. C. (2016). Recommender systems (Vol. 1). Cham: Springer International Publishing."},{"key":"e_1_3_3_1_2_2","volume-title":"Advances in Artificial Intelligence","volume":"2009","author":"Su X.","unstructured":"X. Su and T. M. Khoshgoftaar. 2009. A survey of collaborative filtering techniques. Advances in Artificial Intelligence, vol. 2009."},{"key":"e_1_3_3_1_3_2","volume-title":"Proceedings of the 2000 ACM conference on Computer supported cooperative work (pp. 241-250)","author":"Herlocker J. L.","unstructured":"J. L. Herlocker, J. A. Konstan, and J. Riedl. 2000. Explaining collaborative filtering recommendations. In Proceedings of the 2000 ACM conference on Computer supported cooperative work (pp. 241-250)."},{"key":"e_1_3_3_1_4_2","first-page":"704","volume-title":"Proceedings of the 20th International Conference on Machine Learning (ICML-03)","author":"Si L.","unstructured":"L. Si and R. Jin. 2003. Flexible mixture model for collaborative filtering. In Proceedings of the 20th International Conference on Machine Learning (ICML-03), pp. 704-711."},{"key":"e_1_3_3_1_5_2","first-page":"285","volume-title":"Proceedings of the 10th International Conference on World Wide Web","author":"Sarwar B.","unstructured":"B. Sarwar, G. Karypis, J. Konstan, and J. Riedl. 2001. Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th International Conference on World Wide Web, pp. 285-295."},{"issue":"1","key":"e_1_3_3_1_6_2","first-page":"6694237","article-title":"[Retracted] Personalized Movie Recommendation Method Based on Deep Learning","volume":"2021","author":"Liu J.","year":"2021","unstructured":"J. Liu, W. H. Choi, and J. Liu. 2021. [Retracted] Personalized Movie Recommendation Method Based on Deep Learning. Mathematical Problems in Engineering, 2021(1), 6694237.","journal-title":"Mathematical Problems in Engineering"},{"key":"e_1_3_3_1_7_2","volume-title":"Proceedings of the 2024 12th International Conference on Information and Education Technology (ICIET) (pp. 1-5). IEEE.","author":"Luo Y.","unstructured":"Y. Luo and Z. Wang. 2024. Feature Mining Algorithm for Student Academic Prediction Based on Interpretable Deep Neural Network. In Proceedings of the 2024 12th International Conference on Information and Education Technology (ICIET) (pp. 1-5). IEEE."},{"key":"e_1_3_3_1_8_2","volume-title":"Proceedings of the 2023 6th International Conference on Big Data Technologies (pp. 28-32)","author":"Dai W.","unstructured":"W. Dai, Y. Jiang, C. Mou, and C. Zhang. 2023. An Integrative Paradigm for Enhanced Stroke Prediction: Synergizing XGBoost and xDeepFM Algorithms. In Proceedings of the 2023 6th International Conference on Big Data Technologies (pp. 28-32)."},{"key":"e_1_3_3_1_9_2","volume-title":"Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application (pp. 498-503)","author":"Luo Y.","unstructured":"Y. Luo, R. Zhang, F. Wang, and T. Wei. 2023. Customer Segment Classification Prediction in the Australian Retail Based on Machine Learning Algorithms. In Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application (pp. 498-503)."},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"crossref","unstructured":"S. Li X. Dong D. Ma B. Dang H. Zang and Y. Gong. 2024. Utilizing the lightgbm algorithm for operator user credit assessment research. arXiv preprint arXiv:2403.14483.","DOI":"10.54254\/2755-2721\/75\/20240503"},{"key":"e_1_3_3_1_11_2","first-page":"249","volume-title":"Proceedings of the Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024)","author":"Qu H.","unstructured":"H. Qu, D. Ma, Z. Qi, and N. Zhu. 2024. Advanced deep-learning-based chip design enabling algorithmic and hardware architecture convergence. In Proceedings of the Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024) (Vol. 13171, pp. 249-255). SPIE."},{"key":"e_1_3_3_1_12_2","volume-title":"Proceedings of the 14th ACM Conference on Recommender Systems (pp. 240-248)","author":"Rendle S.","unstructured":"S. Rendle, W. Krichene, L. Zhang, and J. Anderson. 2020. Neural collaborative filtering vs. matrix factorization revisited. In Proceedings of the 14th ACM Conference on Recommender Systems (pp. 240-248)."},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2880197"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"crossref","unstructured":"B. Bhasker. 2020. DNNRec: A novel deep learning based hybrid recommender system. Expert Systems with Applications 144.","DOI":"10.1016\/j.eswa.2019.113054"},{"key":"e_1_3_3_1_15_2","volume-title":"Proceedings of the 2019 International Automatic Control Conference (CACS) (pp. 1-6). IEEE.","author":"Lin Y. R.","unstructured":"Y. R. Lin, W. H. Su, C. H. Lin, B. F. Wu, C. H. Lin, H. Y. Yang, and M. Y. Chen. 2019. Clothing recommendation system based on visual information analytics. In Proceedings of the 2019 International Automatic Control Conference (CACS) (pp. 1-6). IEEE."},{"key":"e_1_3_3_1_16_2","first-page":"202","volume-title":"Proceedings of the Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024)","author":"Luo Y.","unstructured":"Y. Luo, Z. Ye, and R. Lyu. 2024. Detecting student depression on Weibo based on various multimodal fusion methods. In Proceedings of the Fourth International Conference on Signal Processing and Machine Learning (CONF-SPML 2024) (Vol. 13077, pp. 202-207). SPIE."},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"crossref","unstructured":"A. Xiang Z. Qi H. Wang Q. Yang and D. Ma. 2024. A Multimodal Fusion Network For Student Emotion Recognition Based on Transformer and Tensor Product. arXiv preprint arXiv:2403.08511.","DOI":"10.1109\/ICSECE61636.2024.10729485"},{"key":"e_1_3_3_1_18_2","volume-title":"Proceedings of the 2015 2nd International Conference on Electronics and Communication Systems (ICECS) (pp. 1603-1608)","author":"Nagarnaik P.","unstructured":"P. Nagarnaik and A. Thomas. 2015. Survey on recommendation system methods. In Proceedings of the 2015 2nd International Conference on Electronics and Communication Systems (ICECS) (pp. 1603-1608). IEEE."},{"key":"e_1_3_3_1_19_2","unstructured":"S. Li and Y. Xiao. 2024. A Depression Detection Method Based on Multi-Modal Feature Fusion Using Cross-Attention. arXiv preprint arXiv:2407.12825."},{"key":"e_1_3_3_1_20_2","volume-title":"Proceedings of the ACM on Web Conference 2024 (pp. 3632-3642)","author":"Zhang C.","unstructured":"C. Zhang, G. Long, T. Zhou, Z. Zhang, P. Yan, and B. Yang. 2024. When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions. In Proceedings of the ACM on Web Conference 2024 (pp. 3632-3642)."},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/MMUL.2023.3242455"},{"key":"e_1_3_3_1_22_2","unstructured":"I. Hossain S. Puppala M. J. Alam and S. Talukder. 2024. SocialRec: User Activity Based Post Weighted Dynamic Personalized Post Recommendation System in Social Media. arXiv preprint arXiv:2407.09747."},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"crossref","unstructured":"T. Iqbal M. Masud B. Amin C. Feely M. Faherty T. Jones et al. 2024. Towards integration of artificial intelligence into medical devices as a real-time recommender system for personalized healthcare: State-of-the-art and future prospects. Health Sciences Review 100150.","DOI":"10.1016\/j.hsr.2024.100150"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-024-05313-4"},{"key":"e_1_3_3_1_25_2","volume-title":"BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.","author":"Devlin J.","year":"2018","unstructured":"J. Devlin, M. W. Chang, K. Lee, and K. Toutanova. 2018. BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805."},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"crossref","unstructured":"D. Ma M. Wang A. Xiang Z. Qi and Q. Yang. 2024. Transformer-Based Classification Outcome Prediction for Multimodal Stroke Treatment. arXiv preprint arXiv:2404.12634.","DOI":"10.1109\/ICSECE61636.2024.10729409"},{"key":"e_1_3_3_1_27_2","volume-title":"Proceedings of the International Conference on Machine Learning (pp. 1945-1954)","author":"Kusner M. J.","unstructured":"M. J. Kusner, B. Paige, and J. M. Hern\u00e1ndez-Lobato. 2017. Grammar variational autoencoder. In Proceedings of the International Conference on Machine Learning (pp. 1945-1954). PMLR."},{"key":"e_1_3_3_1_28_2","unstructured":"H. Xiao K. Rasul and R. Vollgraf. 2017. Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms. arXiv preprint arXiv:1708.07747."},{"key":"e_1_3_3_1_29_2","unstructured":"D. Lee and H. S. Seung. 2000. Algorithms for non-negative matrix factorization. Advances in Neural Information Processing Systems 13."},{"key":"e_1_3_3_1_30_2","first-page":"3203","volume-title":"Proceedings of IJCAI (Vol. 17","author":"Xue H. J.","unstructured":"H. J. Xue, X. Dai, J. Zhang, S. Huang, and J. Chen. 2017. Deep matrix factorization models for recommender systems. In Proceedings of IJCAI (Vol. 17, pp. 3203-3209)."},{"key":"e_1_3_3_1_31_2","doi-asserted-by":"publisher","DOI":"10.1007\/s41870-020-00553-2"},{"key":"e_1_3_3_1_32_2","doi-asserted-by":"publisher","DOI":"10.3390\/math11040895"},{"key":"e_1_3_3_1_33_2","volume-title":"Proceedings of the International Conference on Machine Learning (pp. 8748-8763)","author":"Radford A.","unstructured":"A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, ... and I. Sutskever. 2021. Learning transferable visual models from natural language supervision. In Proceedings of the International Conference on Machine Learning (pp. 8748-8763). PMLR."},{"key":"e_1_3_3_1_34_2","unstructured":"J. Lu D. Batra D. Parikh and S. Lee. 2019. VilBERT: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks. Advances in Neural Information Processing Systems 32."},{"issue":"2","key":"e_1_3_3_1_35_2","doi-asserted-by":"crossref","first-page":"04023002","DOI":"10.1061\/JMENEA.MEENG-5121","article-title":"Using images to detect, plan, analyze, and coordinate a smart contract in construction","volume":"39","author":"Chen G.","year":"2023","unstructured":"G. Chen, M. Liu, Y. Zhang, Z. Wang, S. M. Hsiang, and C. He. 2023. Using images to detect, plan, analyze, and coordinate a smart contract in construction. Journal of Management in Engineering, 39(2), 04023002.","journal-title":"Journal of Management in Engineering"},{"key":"e_1_3_3_1_36_2","volume-title":"Proceedings of the Construction Research Congress 2022 (pp. 930-939)","author":"He C.","unstructured":"C. He, M. Liu, Z. Wang, G. Chen, Y. Zhang, and S. M. Hsiang. 2022. Facilitating smart contract in project scheduling under uncertainty\u2014A Choquet integral approach. In Proceedings of the Construction Research Congress 2022 (pp. 930-939)."},{"key":"e_1_3_3_1_37_2","article-title":"Bipartite graphs and recommendation systems","author":"Maier C.","year":"2022","unstructured":"C. Maier and D. Simovici. 2022. Bipartite graphs and recommendation systems. Journal of Advances in Information Technology (in print).","journal-title":"Journal of Advances in Information Technology (in print)."},{"issue":"3","key":"e_1_3_3_1_38_2","doi-asserted-by":"crossref","first-page":"518","DOI":"10.12720\/jait.14.3.518-522","article-title":"Recommendation system with content-based filtering in NFT marketplace","volume":"14","author":"Surya Negara E.","year":"2023","unstructured":"E. Surya Negara, et al. 2023. Recommendation system with content-based filtering in NFT marketplace. Journal of Advances in Information Technology, 14(3), 518-522.","journal-title":"Journal of Advances in Information Technology"}],"event":{"name":"AICCC 2024: 2024 the 7th Artificial Intelligence and Cloud Computing Conference","location":"Tokyo Japan","acronym":"AICCC 2024"},"container-title":["Proceedings of the 2024 7th Artificial Intelligence and Cloud Computing Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3719384.3719440","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,9]],"date-time":"2025-07-09T14:45:12Z","timestamp":1752072312000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3719384.3719440"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,14]]},"references-count":38,"alternative-id":["10.1145\/3719384.3719440","10.1145\/3719384"],"URL":"https:\/\/doi.org\/10.1145\/3719384.3719440","relation":{},"subject":[],"published":{"date-parts":[[2024,12,14]]},"assertion":[{"value":"2025-07-09","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}