{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T05:04:50Z","timestamp":1765343090826,"version":"3.46.0"},"publisher-location":"New York, NY, USA","reference-count":62,"publisher":"ACM","funder":[{"name":"Fundamental Research Funds for the Central Universities of China","award":["2024JBGP008,2023YJS168,2024YJS126"],"award-info":[{"award-number":["2024JBGP008,2023YJS168,2024YJS126"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62402031,62072292,61702030"],"award-info":[{"award-number":["62402031,62072292,61702030"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005090","name":"Beijing Nova Program","doi-asserted-by":"publisher","award":["20240484620"],"award-info":[{"award-number":["20240484620"]}],"id":[{"id":"10.13039\/501100005090","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,10,27]]},"DOI":"10.1145\/3746027.3754787","type":"proceedings-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T07:27:39Z","timestamp":1761377259000},"page":"2352-2361","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A Language-Assisted Semantic-Aware Disentangled Method for Link Prediction on Heterogeneous Graphs"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2353-0920","authenticated-orcid":false,"given":"Rongqiang","family":"Fang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China, Key Laboratory of Big Data & Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education, Beijing, China, and School of Computer Science and Technology, Beijing Jiaotong University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2155-0293","authenticated-orcid":false,"given":"Yongqi","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China, Key Laboratory of Big Data & Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education, Beijing, China, and School of Computer Science and Technology, Beijing Jiaotong University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2654-3372","authenticated-orcid":false,"given":"Jidong","family":"Yuan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China, Key Laboratory of Big Data & Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education, Beijing, China, and School of Computer Science and Technology, Beijing Jiaotong University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2128-6442","authenticated-orcid":false,"given":"Hongbo","family":"Cao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China, Key Laboratory of Big Data & Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education, Beijing, China, and School of Computer Science and Technology, Beijing Jiaotong University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1853-4096","authenticated-orcid":false,"given":"Jinkun","family":"Dong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China, Key Laboratory of Big Data & Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education, Beijing, China, and School of Computer Science and Technology, Beijing Jiaotong University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107746"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymeth.2023.11.014"},{"key":"e_1_3_2_2_3_1","volume-title":"Integrating Social and Knowledge Graphs in GNN-Based Recommender Systems. In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 1-8.","author":"Yu Zengyi","year":"2024","unstructured":"Zengyi Yu, Yonggu Wang, Mengfang Hu, and Zihan Wang. 2024. Integrating Social and Knowledge Graphs in GNN-Based Recommender Systems. In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 1-8."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.112290"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128629"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i14.29464"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.osnem.2023.100248"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110589"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.111163"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3661821"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645592"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28708"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645517"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-023-00876-4"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121382"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10447704"},{"key":"e_1_3_2_2_17_1","volume-title":"NESS: Node Embeddings from Static SubGraphs. arXiv preprint arXiv:2303.08958","author":"Ucar Talip","year":"2023","unstructured":"Talip Ucar. 2023. NESS: Node Embeddings from Static SubGraphs. arXiv preprint arXiv:2303.08958 (2023)."},{"key":"e_1_3_2_2_18_1","volume-title":"RW-HeCo: A random walk and network centrality based graph neural network for community detection in heterogeneous networks. Multimedia Tools and Applications","author":"Verma Atul Kumar","year":"2024","unstructured":"Atul Kumar Verma, Mahipal Jadeja, and Saurabh Jayaswal. 2024. RW-HeCo: A random walk and network centrality based graph neural network for community detection in heterogeneous networks. Multimedia Tools and Applications (2024), 1-24."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.127109"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671987"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jag.2024.103709"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681021"},{"key":"e_1_3_2_2_23_1","volume-title":"SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network. arXiv preprint arXiv:2405.01927","author":"Zhou Ziang","year":"2024","unstructured":"Ziang Zhou, Jieming Shi, Renchi Yang, Yuanhang Zou, and Qing Li. 2024. SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network. arXiv preprint arXiv:2405.01927 (2024)."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.11.030"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589335.3651502"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Xiao Wang Houye Ji Chuan Shi Bai Wang Yanfang Ye Peng Cui and Philip S Yu. 2019. Heterogeneous graph attention network. In The world wide web conference. 2022-2032.","DOI":"10.1145\/3308558.3313562"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380027"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16544"},{"key":"e_1_3_2_2_29_1","volume-title":"Heterogeneous Graph Neural Network Focused on Structural Features for Link Prediction. In 2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE). 577-582","author":"Bai Longjie","year":"2024","unstructured":"Longjie Bai, Yongli Wang, and Dongmei Liu. 2024. Heterogeneous Graph Neural Network Focused on Structural Features for Link Prediction. In 2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE). 577-582."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207586"},{"key":"e_1_3_2_2_31_1","volume-title":"Link prediction on heterophilic graphs via disentangled representation learning. arXiv preprint arXiv:2208.01820","author":"Zhou Shijie","year":"2022","unstructured":"Shijie Zhou, Zhimeng Guo, Charu Aggarwal, Xiang Zhang, and Suhang Wang. 2022. Link prediction on heterophilic graphs via disentangled representation learning. arXiv preprint arXiv:2208.01820 (2022)."},{"key":"e_1_3_2_2_32_1","first-page":"20286","article-title":"Factorizable graph convolutional networks","volume":"33","author":"Yang Yiding","year":"2020","unstructured":"Yiding Yang, Zunlei Feng, Mingli Song, and Xinchao Wang. 2020. Factorizable graph convolutional networks. Advances in Neural Information Processing Systems, Vol. 33 (2020), 20286-20296.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_33_1","volume-title":"Meta Structure Search for Link Weight Prediction in Heterogeneous Graphs. In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 5195-5199","author":"Zhang Xiaoou","year":"2024","unstructured":"Xiaoou Zhang, Yang Gao, Yang Liu, Yujia Zhu, Peng Zhang, Chuan Zhou, Qingyun Liu, and Hongyang Chen. 2024. Meta Structure Search for Link Weight Prediction in Heterogeneous Graphs. In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 5195-5199."},{"volume-title":"Database Systems for Advanced Applications","author":"Wu Likang","key":"e_1_3_2_2_34_1","unstructured":"Likang Wu, Zhi Li, Hongke Zhao, Qi Liu, Jun Wang, Mengdi Zhang, and Enhong Chen. 2021. Learning the Implicit Semantic Representation on Graph-Structured Data. In Database Systems for Advanced Applications. Springer International Publishing, Cham, 3-19."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3235944"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6964"},{"key":"e_1_3_2_2_37_1","volume-title":"Maria Sofia Bucarelli, and Fabrizio Silvestri","author":"Di Francesco Andrea Giuseppe","year":"2024","unstructured":"Andrea Giuseppe Di Francesco, Francesco Caso, Maria Sofia Bucarelli, and Fabrizio Silvestri. 2024. Link Prediction under Heterophily: A Physics-Inspired Graph Neural Network Approach. arXiv preprint arXiv:2402.14802 (2024)."},{"key":"e_1_3_2_2_38_1","volume-title":"Adversarially regularized graph autoencoder for graph embedding. arXiv preprint arXiv:1802.04407","author":"Pan Shirui","year":"2018","unstructured":"Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Lina Yao, and Chengqi Zhang. 2018. Adversarially regularized graph autoencoder for graph embedding. arXiv preprint arXiv:1802.04407 (2018)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2022.102902"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118737"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110930"},{"key":"e_1_3_2_2_42_1","volume-title":"Proceedings of the Second Learning on Graphs Conference (Proceedings of Machine Learning Research","volume":"17","author":"Ferrini Francesco","year":"2024","unstructured":"Francesco Ferrini, Antonio Longa, Andrea Passerini, and Manfred Jaeger. 2024. Meta-Path Learning for Multi-Relational Graph Neural Networks. In Proceedings of the Second Learning on Graphs Conference (Proceedings of Machine Learning Research, Vol. 231). PMLR, 1-17."},{"key":"e_1_3_2_2_43_1","volume-title":"Shweta Ann Jacob, and Amirali Salehi-Abari","author":"Louis Paul","year":"2023","unstructured":"Paul Louis, Shweta Ann Jacob, and Amirali Salehi-Abari. 2023. Simplifying subgraph representation learning for scalable link prediction. arXiv preprint arXiv:2301.12562 (2023)."},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3651671.3651684"},{"key":"e_1_3_2_2_45_1","volume-title":"Heterogeneous Graph-based Framework with Disentangled Representations Learning for Multi-target Cross Domain Recommendation. arXiv preprint arXiv:2407.00909","author":"Liu Xiaopeng","year":"2024","unstructured":"Xiaopeng Liu, Juan Zhang, Chongqi Ren, Shenghui Xu, Zhaoming Pan, and Zhimin Zhang. 2024. Heterogeneous Graph-based Framework with Disentangled Representations Learning for Multi-target Cross Domain Recommendation. arXiv preprint arXiv:2407.00909 (2024)."},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-023-06475-x"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121120"},{"key":"e_1_3_2_2_48_1","volume-title":"Link Prediction on Textual Edge Graphs. arXiv preprint arXiv:2405.16606","author":"Ling Chen","year":"2024","unstructured":"Chen Ling, Zhuofeng Li, Yuntong Hu, Zheng Zhang, Zhongyuan Liu, Shuang Zheng, Jian Pei, and Liang Zhao. 2024. Link Prediction on Textual Edge Graphs. arXiv preprint arXiv:2405.16606 (2024)."},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-023-01228-8"},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10446972"},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-024-05895-z"},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_2_53_1","volume-title":"Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084","author":"Reimers Nils","year":"2019","unstructured":"Nils Reimers and Iryna Gurevych. 2019. Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084 (2019)."},{"key":"e_1_3_2_2_54_1","first-page":"2842","volume-title":"HiGPT: Heterogeneous Graph Language Model (KDD '24)","author":"Tang Jiabin","year":"2024","unstructured":"Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Long Xia, Dawei Yin, and Chao Huang. 2024. HiGPT: Heterogeneous Graph Language Model (KDD '24). Association for Computing Machinery, New York, NY, USA, 2842-2853."},{"key":"e_1_3_2_2_55_1","volume-title":"Advances in Neural Information Processing Systems","volume":"31","author":"Zhang Muhan","year":"2018","unstructured":"Muhan Zhang and Yixin Chen. 2018. Link prediction based on graph neural networks. Advances in Neural Information Processing Systems, Vol. 31 (2018)."},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-022-12943-8"},{"key":"e_1_3_2_2_57_1","unstructured":"Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio et al. 2017. Graph attention networks. stat Vol. 1050 20 (2017) 10-48550."},{"key":"e_1_3_2_2_58_1","volume-title":"International Conference on Learning Representations.","author":"Chien Eli","year":"2021","unstructured":"Eli Chien, Jianhao Peng, Pan Li, and Olgica Milenkovic. 2021. Adaptive universal generalized pagerank graph neural network. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_59_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16514"},{"key":"e_1_3_2_2_60_1","volume-title":"International conference on machine learning. PMLR, 4212-4221","author":"Ma Jianxin","year":"2019","unstructured":"Jianxin Ma, Peng Cui, Kun Kuang, Xin Wang, and Wenwu Zhu. 2019. Disentangled graph convolutional networks. In International conference on machine learning. PMLR, 4212-4221."},{"key":"e_1_3_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2024.109216"},{"key":"e_1_3_2_2_62_1","volume-title":"Advances in Neural Information Processing Systems","volume":"29","author":"Salimans Tim","year":"2016","unstructured":"Tim Salimans and Durk P Kingma. 2016. Weight normalization: A simple reparameterization to accelerate training of deep neural networks. Advances in Neural Information Processing Systems, Vol. 29 (2016)."}],"event":{"name":"MM '25: The 33rd ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Dublin Ireland","acronym":"MM '25"},"container-title":["Proceedings of the 33rd ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746027.3754787","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T05:00:36Z","timestamp":1765342836000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746027.3754787"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":62,"alternative-id":["10.1145\/3746027.3754787","10.1145\/3746027"],"URL":"https:\/\/doi.org\/10.1145\/3746027.3754787","relation":{},"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"2025-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}