{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T14:28:19Z","timestamp":1766068099346,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":47,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T00:00:00Z","timestamp":1729468800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"The Project of Science and Technology Research and Development Plan of China Railway Corporation","award":["N2023J044"],"award-info":[{"award-number":["N2023J044"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,21]]},"DOI":"10.1145\/3627673.3679785","type":"proceedings-article","created":{"date-parts":[[2024,10,20]],"date-time":"2024-10-20T19:34:21Z","timestamp":1729452861000},"page":"706-716","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Graph Local Homophily Network for Anomaly Detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1586-7040","authenticated-orcid":false,"given":"Ronghui","family":"Guo","sequence":"first","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8777-0678","authenticated-orcid":false,"given":"Minghui","family":"Zou","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8972-2824","authenticated-orcid":false,"given":"Sai","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3931-3886","authenticated-orcid":false,"given":"Xiaowang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5954-3593","authenticated-orcid":false,"given":"Zhizhi","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8158-7453","authenticated-orcid":false,"given":"Zhiyong","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University, Tianjin, China"}]}],"member":"320","published-online":{"date-parts":[[2024,10,21]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9--15","volume":"29","author":"Abu-El-Haija Sami","year":"2019","unstructured":"Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, and Aram Galstyan. 2019. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9--15 June 2019, Long Beach, California, USA (Proceedings of Machine Learning Research, Vol. 97), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 21--29. http:\/\/proceedings.mlr.press\/v97\/abu-el-haija19a.html"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16514"},{"key":"e_1_3_2_1_3_1","volume-title":"2nd International Conference on Learning Representations, ICLR","author":"Bruna Joan","year":"2014","unstructured":"Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann LeCun. 2014. Spectral Networks and Locally Connected Networks on Graphs. In 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14--16, 2014, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds.). http:\/\/arxiv.org\/abs\/1312.6203"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/270"},{"key":"e_1_3_2_1_5_1","unstructured":"Sudhanshu Chanpuriya and Cameron Musco. 2022. Simplified Graph Convolution with Heterophily. In NeurIPS. http:\/\/papers.nips.cc\/paper_files\/paper\/2022\/hash\/ae07d152c51ea2ddae65aa7192eb5ff7-Abstract-Conference.html"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3200459"},{"key":"e_1_3_2_1_7_1","unstructured":"Nan Chen Zemin Liu Bryan Hooi Bingsheng He Rizal Fathony Jun Hu and Jia Chen. 2024. Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision. In The Twelfth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=elMKXvhhQ9"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/395"},{"key":"e_1_3_2_1_9_1","volume-title":"Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016","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. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5--10, 2016, Barcelona, Spain, Daniel D. Lee, Masashi Sugiyama, Ulrike von Luxburg, Isabelle Guyon, and Roman Garnett (Eds.). 3837--3845. https:\/\/proceedings.neurips.cc\/paper\/2016\/hash\/04df4d434d481c5bb723be1b6df1ee65-Abstract.html"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411903"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512201"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583268"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570377"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512178"},{"key":"e_1_3_2_1_15_1","unstructured":"Xuanwen Huang Yang Yang Yang Wang Chunping Wang Zhisheng Zhang Jiarong Xu Lei Chen and Michalis Vazirgiannis. 2022. DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection. In NeurIPS. http:\/\/papers.nips.cc\/paper_files\/paper\/2022\/hash\/8f1918f71972789db39ec0d85bb31110-Abstract-Datasets_and_Benchmarks.html"},{"key":"e_1_3_2_1_16_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2015","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings, Yoshua Bengio and Yann LeCun (Eds.). http:\/\/arxiv.org\/abs\/1412.6980"},{"key":"e_1_3_2_1_17_1","volume-title":"Kipf and Max Welling","author":"Thomas","year":"2017","unstructured":"Thomas N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24--26, 2017, Conference Track Proceedings. OpenReview.net. https:\/\/openreview.net\/forum?id=SJU4ayYgl"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449989"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3272010"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401253"},{"key":"e_1_3_2_1_22_1","unstructured":"Sitao Luan Chenqing Hua Qincheng Lu Jiaqi Zhu Mingde Zhao Shuyuan Zhang Xiao-Wen Chang and Doina Precup. 2022. Revisiting Heterophily For Graph Neural Networks. In NeurIPS. http:\/\/papers.nips.cc\/paper_files\/paper\/2022\/hash\/092359ce5cf60a80e882378944bf1be4-Abstract-Conference.html"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3118815"},{"key":"e_1_3_2_1_24_1","volume-title":"A Wavelet Tour of Signal Processing","author":"Mallat St\u00e9phane","unstructured":"St\u00e9phane Mallat. 1999. A Wavelet Tour of Signal Processing, 2nd Edition. Academic Press.","edition":"2"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2488388.2488466"},{"key":"e_1_3_2_1_26_1","volume-title":"Birds of a feather: Homophily in social networks. Annual review of sociology","author":"McPherson Miller","year":"2001","unstructured":"Miller McPherson, Lynn Smith-Lovin, and James M Cook. 2001. Birds of a feather: Homophily in social networks. Annual review of sociology, Vol. 27, 1 (2001), 415--444."},{"key":"e_1_3_2_1_27_1","volume-title":"Revisiting Graph Neural Networks: All We Have is Low-Pass Filters. CoRR","author":"Takanori Maehara Hoang","year":"2019","unstructured":"Hoang NT and Takanori Maehara. 2019. Revisiting Graph Neural Networks: All We Have is Low-Pass Filters. CoRR, Vol. abs\/1905.09550 (2019). showeprint[arXiv]1905.09550 http:\/\/arxiv.org\/abs\/1905.09550"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783370"},{"key":"e_1_3_2_1_29_1","volume-title":"Homophily-heterophily: Relational concepts for communication research. Public opinion quarterly","author":"Rogers Everett M","year":"1970","unstructured":"Everett M Rogers and Dilip K Bhowmik. 1970. Homophily-heterophily: Relational concepts for communication research. Public opinion quarterly, Vol. 34, 4 (1970), 523--538."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512195"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2235192"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20385"},{"key":"e_1_3_2_1_33_1","volume-title":"Rethinking Graph Neural Networks for Anomaly Detection. In International Conference on Machine Learning, ICML 2022","volume":"21089","author":"Tang Jianheng","year":"2022","unstructured":"Jianheng Tang, Jiajin Li, Ziqi Gao, and Jia Li. 2022. Rethinking Graph Neural Networks for Anomaly Detection. In International Conference on Machine Learning, ICML 2022, 17--23 July 2022, Baltimore, Maryland, USA (Proceedings of Machine Learning Research, Vol. 162), Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesv\u00e1ri, Gang Niu, and Sivan Sabato (Eds.). PMLR, 21076--21089. https:\/\/proceedings.mlr.press\/v162\/tang22b.html"},{"key":"e_1_3_2_1_34_1","volume-title":"Representation Learning with Contrastive Predictive Coding. CoRR","author":"van den Oord A\u00e4ron","year":"2018","unstructured":"A\u00e4ron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation Learning with Contrastive Predictive Coding. CoRR, Vol. abs\/1807.03748 (2018). showeprint[arXiv]1807.03748 http:\/\/arxiv.org\/abs\/1807.03748"},{"key":"e_1_3_2_1_35_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, Vol. 9, 11 (2008).","journal-title":"Journal of machine learning research"},{"key":"e_1_3_2_1_36_1","volume-title":"6th International Conference on Learning Representations, ICLR","author":"Velickovic Petar","year":"2018","unstructured":"Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2018. Graph Attention Networks. In 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings. OpenReview.net. https:\/\/openreview.net\/forum?id=rJXMpikCZ"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308560.3316586"},{"key":"e_1_3_2_1_38_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_1_39_1","volume-title":"International Conference on Machine Learning, ICML 2022","volume":"23362","author":"Wang Xiyuan","year":"2022","unstructured":"Xiyuan Wang and Muhan Zhang. 2022. How Powerful are Spectral Graph Neural Networks. In International Conference on Machine Learning, ICML 2022, 17--23 July 2022, Baltimore, Maryland, USA (Proceedings of Machine Learning Research, Vol. 162), Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesv\u00e1ri, Gang Niu, and Sivan Sabato (Eds.). PMLR, 23341--23362. https:\/\/proceedings.mlr.press\/v162\/wang22am.html"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583373"},{"key":"e_1_3_2_1_41_1","volume-title":"Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9--15","volume":"6871","author":"Wu Felix","year":"2019","unstructured":"Felix Wu, Amauri H. Souza Jr., Tianyi Zhang, Christopher Fifty, Tao Yu, and Kilian Q. Weinberger. 2019. Simplifying Graph Convolutional Networks. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9--15 June 2019, Long Beach, California, USA (Proceedings of Machine Learning Research, Vol. 97), Kamalika Chaudhuri and Ruslan Salakhutdinov (Eds.). PMLR, 6861--6871. http:\/\/proceedings.mlr.press\/v97\/wu19e.html"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1609\/AAAI.V38I8.28773"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512122"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM51629.2021.00098"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3102609"},{"key":"e_1_3_2_1_46_1","volume-title":"Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems","author":"Zhu Jiong","year":"2020","unstructured":"Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, and Danai Koutra. 2020. Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6--12, 2020, virtual, Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin (Eds.). https:\/\/proceedings.neurips.cc\/paper\/2020\/hash\/58ae23d878a47004366189884c2f8440-Abstract.html"},{"key":"e_1_3_2_1_47_1","volume-title":"Partitioning Message Passing for Graph Fraud Detection. In The Twelfth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=tEgrUrUuwA","author":"Zhuo Wei","year":"2024","unstructured":"Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, and Jia Chen. 2024. Partitioning Message Passing for Graph Fraud Detection. In The Twelfth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=tEgrUrUuwA"}],"event":{"name":"CIKM '24: The 33rd ACM International Conference on Information and Knowledge Management","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Boise ID USA","acronym":"CIKM '24"},"container-title":["Proceedings of the 33rd ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627673.3679785","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3627673.3679785","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:58:28Z","timestamp":1750294708000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627673.3679785"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,21]]},"references-count":47,"alternative-id":["10.1145\/3627673.3679785","10.1145\/3627673"],"URL":"https:\/\/doi.org\/10.1145\/3627673.3679785","relation":{},"subject":[],"published":{"date-parts":[[2024,10,21]]},"assertion":[{"value":"2024-10-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}