{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T13:35:32Z","timestamp":1774964132960,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,7,20]],"date-time":"2025-07-20T00:00:00Z","timestamp":1752969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,7,20]]},"DOI":"10.1145\/3690624.3709396","type":"proceedings-article","created":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T18:42:22Z","timestamp":1743792142000},"page":"2448-2457","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["LinkSAGE: Optimizing Job Matching Using Graph Neural Networks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0866-8801","authenticated-orcid":false,"given":"Ping","family":"Liu","sequence":"first","affiliation":[{"name":"LinkedIn Corporation, Sunnyvale, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8307-3896","authenticated-orcid":false,"given":"Haichao","family":"Wei","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Santa Clara, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-3967-2683","authenticated-orcid":false,"given":"Xiaochen","family":"Hou","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Mountain View, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-5258-6523","authenticated-orcid":false,"given":"Jianqiang","family":"Shen","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Mountain View, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7515-5430","authenticated-orcid":false,"given":"Shihai","family":"He","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Sunnyvale, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9323-6404","authenticated-orcid":false,"given":"Qianqi","family":"Shen","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Sunnyvale, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1086-1919","authenticated-orcid":false,"given":"Zhujun","family":"Chen","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, San Francisco, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8171-7656","authenticated-orcid":false,"given":"Fedor","family":"Borisyuk","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Sunnyvale, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2306-0957","authenticated-orcid":false,"given":"Daniel","family":"Hewlett","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Sunnyvale, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2336-7695","authenticated-orcid":false,"given":"Liang","family":"Wu","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Sunnyvale, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8769-3159","authenticated-orcid":false,"given":"Srikant","family":"Veeraraghavan","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Sunnyvale, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9320-6423","authenticated-orcid":false,"given":"Alex","family":"Tsun","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Sunnyvale, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0115-4603","authenticated-orcid":false,"given":"Chengming","family":"Jiang","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Mountain View, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6510-1222","authenticated-orcid":false,"given":"Wenjing","family":"Zhang","sequence":"additional","affiliation":[{"name":"LinkedIn Corporation, Sunnyvale, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2025,7,20]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637528.3671566"},{"key":"e_1_3_2_2_2_1","volume-title":"Meta-graph: Few shot link prediction via meta learning. arXiv preprint arXiv:1912.09867","author":"Bose Avishek Joey","year":"2019","unstructured":"Avishek Joey Bose, Ankit Jain, Piero Molino, and William L Hamilton. 2019. Meta-graph: Few shot link prediction via meta learning. arXiv preprint arXiv:1912.09867 (2019)."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3522672"},{"key":"e_1_3_2_2_4_1","volume-title":"Adaptive Universal Generalized PageRank Graph Neural Network. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=n6jl7fLxrP","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. https:\/\/openreview.net\/forum?id=n6jl7fLxrP"},{"key":"e_1_3_2_2_5_1","volume-title":"Job recommender systems: A review. arXiv preprint arXiv:2111.13576","author":"Ruijt Corn\u00e9 De","year":"2021","unstructured":"Corn\u00e9 De Ruijt and Sandjai Bhulai. 2021. Job recommender systems: A review. arXiv preprint arXiv:2111.13576 (2021)."},{"key":"e_1_3_2_2_6_1","volume-title":"Convolutional neural networks on graphs with fast localized spectral filtering. Advances in neural information processing systems","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, Vol. 29 (2016)."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3481916"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330958"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539080"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013558"},{"key":"e_1_3_2_2_11_1","volume-title":"Fast Graph Representation Learning with PyTorch Geometric. In ICLR Workshop on Representation Learning on Graphs and Manifolds.","author":"Fey Matthias","unstructured":"Matthias Fey and Jan E. Lenssen. 2019. Fast Graph Representation Learning with PyTorch Geometric. In ICLR Workshop on Representation Learning on Graphs and Manifolds."},{"key":"e_1_3_2_2_12_1","volume-title":"Protein interface prediction using graph convolutional networks. Advances in neural information processing systems","author":"Fout Alex","year":"2017","unstructured":"Alex Fout, Jonathon Byrd, Basir Shariat, and Asa Ben-Hur. 2017. Protein interface prediction using graph convolutional networks. Advances in neural information processing systems, Vol. 30 (2017)."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441824"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347001"},{"key":"e_1_3_2_2_15_1","volume-title":"Inductive representation learning on large graphs. Advances in neural information processing systems","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, Vol. 30 (2017)."},{"key":"e_1_3_2_2_16_1","volume-title":"A hybrid approach to managing job offers and candidates. Information processing & management","author":"Kessler R\u00e9my","year":"2012","unstructured":"R\u00e9my Kessler, Nicolas B\u00e9chet, Mathieu Roche, Juan-Manuel Torres-Moreno, and Marc El-B\u00e8ze. 2012. A hybrid approach to managing job offers and candidates. Information processing & management, Vol. 48, 6 (2012), 1124--1135."},{"key":"e_1_3_2_2_17_1","volume-title":"Semi-Supervised Classification with Graph Convolutional Networks. arXiv preprint arXiv:1609.02907","author":"Kipf Thomas N","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_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357949"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359284"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2017.8122984"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347016"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467276"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411910"},{"key":"e_1_3_2_2_24_1","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume":"30","author":"Maas Andrew L","year":"2013","unstructured":"Andrew L Maas, Awni Y Hannun, Andrew Y Ng, et al. 2013. Rectifier nonlinearities improve neural network acoustic models. In ICML, Vol. 30. 3.","journal-title":"ICML"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10796-019-09929-7"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/icABCD49160.2020.9183813"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CCIS48116.2019.9073723"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210025"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2017.04.002"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.12416"},{"key":"e_1_3_2_2_31_1","volume-title":"Temporal Graph Networks for Deep Learning on Dynamic Graphs. In ICML 2020 Workshop on Graph Representation Learning.","author":"Rossi Emanuele","year":"2020","unstructured":"Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, and Michael Bronstein. 2020. Temporal Graph Networks for Deep Learning on Dynamic Graphs. In ICML 2020 Workshop on Graph Representation Learning."},{"key":"e_1_3_2_2_32_1","unstructured":"Alex Samylkin. 2022. DeepGNN is a framework for training machine learning models on large scale graph data. https:\/\/github.com\/microsoft\/DeepGNN"},{"key":"e_1_3_2_2_33_1","volume-title":"International conference on learning representations.","author":"Satorras Victor Garcia","year":"2018","unstructured":"Victor Garcia Satorras and Joan Bruna Estrach. 2018. Few-shot learning with graph neural networks. In International conference on learning representations."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3627673.3679953"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583340"},{"key":"e_1_3_2_2_36_1","volume-title":"Graph Attention Networks. In International Conference on Learning Representations.","author":"Veli\u010dkovi\u0107 Petar","year":"2018","unstructured":"Petar Veli\u010dkovi\u0107, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2018. Graph Attention Networks. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_37_1","volume-title":"Highly-Performant Package for Graph Neural Networks. arXiv preprint arXiv:1909.01315","author":"Wang Minjie","year":"2019","unstructured":"Minjie Wang, Da Zheng, Zihao Ye, Quan Gan, Mufei Li, Xiang Song, Jinjing Zhou, Chao Ma, Lingfan Yu, Yu Gai, Tianjun Xiao, Tong He, George Karypis, Jinyang Li, and Zheng Zhang. 2019. Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks. arXiv preprint arXiv:1909.01315 (2019)."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3547333"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5455"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26283"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330961"}],"event":{"name":"KDD '25: The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Toronto ON Canada","acronym":"KDD '25","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3690624.3709396","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3690624.3709396","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,16]],"date-time":"2025-08-16T15:36:42Z","timestamp":1755358602000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3690624.3709396"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,20]]},"references-count":42,"alternative-id":["10.1145\/3690624.3709396","10.1145\/3690624"],"URL":"https:\/\/doi.org\/10.1145\/3690624.3709396","relation":{},"subject":[],"published":{"date-parts":[[2025,7,20]]},"assertion":[{"value":"2025-07-20","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}