{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T10:01:48Z","timestamp":1775815308310,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T00:00:00Z","timestamp":1628899200000},"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":[[2021,8,14]]},"DOI":"10.1145\/3447548.3467065","type":"proceedings-article","created":{"date-parts":[[2021,8,13]],"date-time":"2021-08-13T18:21:39Z","timestamp":1628878899000},"page":"3670-3678","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":31,"title":["Live-Streaming Fraud Detection: A Heterogeneous Graph Neural Network Approach"],"prefix":"10.1145","author":[{"given":"Zhao","family":"Li","sequence":"first","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Haishuai","family":"Wang","sequence":"additional","affiliation":[{"name":"Fairfield University, Fairfield, CT, USA"}]},{"given":"Peng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Guangzhou University, Guangzhou, China"}]},{"given":"Pengrui","family":"Hui","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Jiaming","family":"Huang","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Jian","family":"Liao","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}]},{"given":"Ji","family":"Zhang","sequence":"additional","affiliation":[{"name":"The University of Southern Queensland, Toowoomba, QLD, Australia"}]},{"given":"Jiajun","family":"Bu","sequence":"additional","affiliation":[{"name":"Zhejiang University, Hangzhou, China"}]}],"member":"320","published-online":{"date-parts":[[2021,8,14]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2660267.2660269"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/IRI.2018.00025"},{"key":"e_1_3_2_2_3_1","volume-title":"International Conference on Machine Learning. PMLR, 1263--1272","author":"Gilmer Justin","year":"2017","unstructured":"Justin Gilmer , Samuel S Schoenholz , Patrick F Riley , Oriol Vinyals , and George E Dahl . 2017 . Neural message passing for quantum chemistry . In International Conference on Machine Learning. PMLR, 1263--1272 . Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl. 2017. Neural message passing for quantum chemistry. In International Conference on Machine Learning. PMLR, 1263--1272."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313533"},{"key":"e_1_3_2_2_5_1","volume-title":"Inductive representation learning on large graphs. arXiv preprint arXiv:1706.02216","author":"Hamilton William L","year":"2017","unstructured":"William L Hamilton , Rex Ying , and Jure Leskovec . 2017. Inductive representation learning on large graphs. arXiv preprint arXiv:1706.02216 ( 2017 ). William L Hamilton, Rex Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. arXiv preprint arXiv:1706.02216 (2017)."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jisa.2018.07.009"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380027"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2484313.2484330"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2020.102251"},{"key":"e_1_3_2_2_10_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 ). 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_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2957306"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3272010"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3174040"},{"key":"e_1_3_2_2_14_1","volume-title":"Proceedings of ACM SIGKDD conference","author":"Ma Jun","year":"2018","unstructured":"Jun Ma , Danqing Zhang , Yun Wang , Yan Zhang , and Alexey Pozdnoukhov . 2018 . GraphRAD: a graph-based risky account detection system . In Proceedings of ACM SIGKDD conference , London, UK. 9. Jun Ma, Danqing Zhang, Yun Wang, Yan Zhang, and Alexey Pozdnoukhov. 2018. GraphRAD: a graph-based risky account detection system. In Proceedings of ACM SIGKDD conference, London, UK. 9."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806647"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2627438"},{"key":"e_1_3_2_2_17_1","volume-title":"xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs. arXiv preprint arXiv:2011.12193","author":"Rao Susie Xi","year":"2020","unstructured":"Susie Xi Rao , Shuai Zhang , Zhichao Han , Zitao Zhang , Wei Min , Zhiyao Chen , Yinan Shan , Yang Zhao , and Ce Zhang . 2020. xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs. arXiv preprint arXiv:2011.12193 ( 2020 ). Susie Xi Rao, Shuai Zhang, Zhichao Han, Zitao Zhang, Wei Min, Zhiyao Chen, Yinan Shan, Yang Zhao, and Ce Zhang. 2020. xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs. arXiv preprint arXiv:2011.12193 (2020)."},{"key":"e_1_3_2_2_18_1","volume-title":"Anomaly Detection in Car-Booking Graphs. In 2018 IEEE International Conference on Data Mining Workshops. 604--607","author":"Shchur Oleksandr","year":"2018","unstructured":"Oleksandr Shchur , Aleksandar Bojchevski , Mohamed Farghal , Stephan G\u00fcnnemann , and Yusuf Saber . 2018 . Anomaly Detection in Car-Booking Graphs. In 2018 IEEE International Conference on Data Mining Workshops. 604--607 . Oleksandr Shchur, Aleksandar Bojchevski, Mohamed Farghal, Stephan G\u00fcnnemann, and Yusuf Saber. 2018. Anomaly Detection in Car-Booking Graphs. In 2018 IEEE International Conference on Data Mining Workshops. 604--607."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186079"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.14778\/3402707.3402736"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339738"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505581"},{"key":"e_1_3_2_2_23_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez ?ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008.  Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez ?ukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in neural information processing systems. 5998--6008."},{"key":"e_1_3_2_2_24_1","volume-title":"Graph attention networks. arXiv preprint arXiv:1710.10903","author":"Cucurull Guillem","year":"2017","unstructured":"Guillem Cucurull , Arantxa Casanova , Adriana Romero , Pietro Lio , and Yoshua Bengio . 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 ( 2017 ). Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"crossref","unstructured":"Haobo Wang Zhao Li Jiaming Huang Pengrui Hui Weiwei Liu Tianlei Hu and Gang Chen. 2020. Collaboration based multi-label propagation for fraud detection. In IJCAI .  Haobo Wang Zhao Li Jiaming Huang Pengrui Hui Weiwei Liu Tianlei Hu and Gang Chen. 2020. Collaboration based multi-label propagation for fraud detection. In IJCAI .","DOI":"10.24963\/ijcai.2020\/343"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308560.3316586"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313562"},{"key":"e_1_3_2_2_28_1","volume-title":"Claudio Bellei, Tom Robinson, and Charles E Leiserson.","author":"Weber Mark","year":"2019","unstructured":"Mark Weber , Giacomo Domeniconi , Jie Chen , Daniel Karl I Weidele , Claudio Bellei, Tom Robinson, and Charles E Leiserson. 2019 . Anti-money laundering in bitcoin: Experimenting with graph convolutional networks for financial forensics. arXiv preprint arXiv:1908.02591 (2019). Mark Weber, Giacomo Domeniconi, Jie Chen, Daniel Karl I Weidele, Claudio Bellei, Tom Robinson, and Charles E Leiserson. 2019. Anti-money laundering in bitcoin: Experimenting with graph convolutional networks for financial forensics. arXiv preprint arXiv:1908.02591 (2019)."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366424.3391266"},{"key":"e_1_3_2_2_30_1","volume-title":"Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark","author":"Yang Carl","year":"2020","unstructured":"Carl Yang , Yuxin Xiao , Yu Zhang , Yizhou Sun , and Jiawei Han . 2020. Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark . IEEE Transactions on Knowledge and Data Engineering ( 2020 ). Carl Yang, Yuxin Xiao, Yu Zhang, Yizhou Sun, and Jiawei Han. 2020. Heterogeneous Network Representation Learning: A Unified Framework with Survey and Benchmark. IEEE Transactions on Knowledge and Data Engineering (2020)."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330961"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"crossref","unstructured":"Mengchen Zhao Zhao Li Bo An Haifeng Lu Yifan Yang and Chen Chu. 2018. Impression Allocation for Combating Fraud in E-commerce Via Deep Reinforcement Learning with Action Norm Penalty.. In IJCAI. 3940--3946.  Mengchen Zhao Zhao Li Bo An Haifeng Lu Yifan Yang and Chen Chu. 2018. Impression Allocation for Combating Fraud in E-commerce Via Deep Reinforcement Learning with Action Norm Penalty.. In IJCAI. 3940--3946.","DOI":"10.24963\/ijcai.2018\/548"}],"event":{"name":"KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Virtual Event Singapore","acronym":"KDD '21","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 27th ACM SIGKDD Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467065","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3447548.3467065","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:25:10Z","timestamp":1750195510000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467065"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,14]]},"references-count":32,"alternative-id":["10.1145\/3447548.3467065","10.1145\/3447548"],"URL":"https:\/\/doi.org\/10.1145\/3447548.3467065","relation":{},"subject":[],"published":{"date-parts":[[2021,8,14]]},"assertion":[{"value":"2021-08-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}