{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:47:23Z","timestamp":1765500443350,"version":"3.48.0"},"publisher-location":"New York, NY, USA","reference-count":28,"publisher":"ACM","funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2022-NR068758"],"award-info":[{"award-number":["RS-2022-NR068758"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,10]]},"DOI":"10.1145\/3746252.3761099","type":"proceedings-article","created":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T18:37:32Z","timestamp":1762799852000},"page":"1334-1343","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-4759-108X","authenticated-orcid":false,"given":"Jongwoo","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Industrial & Systems Engineering,, KAIST, Daejon, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2631-0456","authenticated-orcid":false,"given":"Seongyeub","family":"Chu","sequence":"additional","affiliation":[{"name":"Graduate School of Data Science, KAIST, Daejeon, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6040-6891","authenticated-orcid":false,"given":"Hyeongmin","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Industrial & Systems Engineering, KAIST, Daejeon, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2257-3454","authenticated-orcid":false,"given":"Bryan","family":"Wong","sequence":"additional","affiliation":[{"name":"Graduate School of Data Science, KAIST, Daejeon, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6395-5996","authenticated-orcid":false,"given":"Keejun","family":"Han","sequence":"additional","affiliation":[{"name":"School of Computer Engineering, Hansung University, Seoul, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1784-8983","authenticated-orcid":false,"given":"Mun Yong","family":"Yi","sequence":"additional","affiliation":[{"name":"Department of Industrial & Systems Engineering, KAIST, Daejeon, Republic of Korea"}]}],"member":"320","published-online":{"date-parts":[[2025,11,10]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Yoshua Bengio Nicholas L\u00e9onard and Aaron Courville. 2013. Estimating or propagating gradients through stochastic neurons for conditional computation. In arXiv preprint arXiv:1308.3432."},{"key":"e_1_3_2_1_2_1","volume-title":"Hammerla","author":"Busbridge Dan","year":"2019","unstructured":"Dan Busbridge, Dane Sherburn, Pietro Cavallo, and Nils Y. Hammerla. 2019. Relational Graph Attention Networks. arXiv preprint arXiv:1904.05811 (2019)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-29551-6_59"},{"key":"e_1_3_2_1_4_1","unstructured":"M. Chen Y. Zhang X. Kou Y. Li and Y. Zhang. 2021. R-GAT: Relational Graph Attention Network for Multi-Relational Graphs. arXiv preprint arXiv:2109.05922 (2021)."},{"key":"e_1_3_2_1_5_1","volume-title":"Convolutional neural networks on graphs with fast localized spectral filtering. Advances in Neural Information Processing Systems 29","author":"Defferrard Micha\u00ebl","year":"2016","unstructured":"Micha\u00ebl Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. Advances in Neural Information Processing Systems 29 (2016)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098036"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313660"},{"key":"e_1_3_2_1_8_1","volume-title":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. 1797-1806","author":"Lee Wang-Chien","year":"2017","unstructured":"Tao-yang Fu, Wang-Chien Lee, and Zhen Lei. 2017. Hin2vec: Explore meta-paths in heterogeneous information networks for representation learning. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. 1797-1806."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.11.030"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380297"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110930"},{"key":"e_1_3_2_1_12_1","volume-title":"Inductive representation learning on large graphs. Advances in Neural Information Processing Systems 30","author":"Hamilton Will","year":"2017","unstructured":"Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. Advances in Neural Information Processing Systems 30 (2017)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5833"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380027"},{"key":"e_1_3_2_1_15_1","volume-title":"Categorical reparameterization with gumbel-softmax. arXiv preprint arXiv:1611.01144","author":"Jang Eric","year":"2016","unstructured":"Eric Jang, Shixiang Gu, and Ben Poole. 2016. Categorical reparameterization with gumbel-softmax. arXiv preprint arXiv:1611.01144 (2016)."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3472956"},{"key":"e_1_3_2_1_17_1","volume-title":"Kipf and Max Welling","author":"Thomas","year":"2016","unstructured":"Thomas N. Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_1_18_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"32","author":"Li Q.","unstructured":"Q. Li, Z. Han, and X. M. Wu. 2018. Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 32."},{"key":"e_1_3_2_1_19_1","volume-title":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 932-940","author":"Liu Ninghao","year":"2019","unstructured":"Ninghao Liu, Qiaoyu Tan, Yuening Li, Hongxia Yang, Jingren Zhou, and Xia Hu. 2019. Is a single vector enough? exploring node polysemy for network embedding. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 932-940."},{"key":"e_1_3_2_1_20_1","volume-title":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 1150-1160","author":"Lv Qingsong","year":"2021","unstructured":"Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jianguo Jiang, Yuxiao Dong, and Jie Tang. 2021. Are we really making much progress? revisiting, benchmarking and refining heterogeneous graph neural networks. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 1150-1160."},{"key":"e_1_3_2_1_21_1","volume-title":"Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781","author":"Mikolov Tomas","year":"2013","unstructured":"Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403196"},{"key":"e_1_3_2_1_23_1","volume-title":"MHNF: Multihop Heterogeneous Neighborhood information Fusion graph representation learning. arXiv:2106.09289 [cs.LG]","author":"Sun Yundong","year":"2022","unstructured":"Yundong Sun, Dongjie Zhu, Haiwen Du, and Zhaoshuo Tian. 2022. MHNF: Multihop Heterogeneous Neighborhood information Fusion graph representation learning. arXiv:2106.09289 [cs.LG]"},{"key":"e_1_3_2_1_24_1","article-title":"Visualizing data using t-SNE","volume":"9","author":"der Maaten Laurens Van","year":"2008","unstructured":"Laurens Van der Maaten and Geoffrey Hinton. 2008. Visualizing data using t-SNE. Journal of Machine Learning Research 9, 11 (2008).","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_25_1","volume-title":"Graph attention networks. stat 1050, 20","author":"Velickovic Petar","year":"2017","unstructured":"Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. Graph attention networks. stat 1050, 20 (2017), 10-48550."},{"volume-title":"The World Wide Web Conference. 2022-2032","author":"Wang Xiao","key":"e_1_3_2_1_26_1","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."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467415"},{"key":"e_1_3_2_1_28_1","first-page":"1","article-title":"Graph Transformer Networks","volume":"39","author":"Yun S.","year":"2019","unstructured":"S. Yun, M. Jeong, R. Kim, J. Kang, and H. J. Kim. 2019. Graph Transformer Networks. In Advances in Neural Information Processing Systems, Vol. 39. 1-12.","journal-title":"Advances in Neural Information Processing Systems"}],"event":{"name":"CIKM '25: The 34th ACM International Conference on Information and Knowledge Management","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Seoul Republic of Korea","acronym":"CIKM '25"},"container-title":["Proceedings of the 34th ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746252.3761099","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:44:44Z","timestamp":1765500284000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746252.3761099"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,10]]},"references-count":28,"alternative-id":["10.1145\/3746252.3761099","10.1145\/3746252"],"URL":"https:\/\/doi.org\/10.1145\/3746252.3761099","relation":{},"subject":[],"published":{"date-parts":[[2025,11,10]]},"assertion":[{"value":"2025-11-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}