{"type":"ScholarlyArticle","title":"Implicit Anomaly Subgraph Detection (IASD) in Multi-Domain Attribute Networks","authors":[{"name":"Ying Sun","slug":"ying-sun","given":"Ying","family":"Sun","affiliation":"Tianjin University; Inner Mongolia University of Science and Technology"}],"abstract":"Anomaly subgraph detection is a vital task in various real applications. However, with the advancement of AI technology, it faces new challenges: 1) Anomaly features are often deeply hidden within large datasets, and 2) Anomaly detection approaches are required to unveil the mechanisms behind anomaly generation.\r\nOur study focuses on detecting hidden anomaly subgraphs within big data and offering improved explanations for the root cause of anomalies by integrating multi-domain datasets.","doi":"10.24963/ijcai.2024/970","url":"https://ijcai.org/proceedings/2024/970","pdf":"https://ijcai.org/proceedings/2024/0970.pdf","markdown":"https://ijcai.org/proceedings/2024/970.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/970","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":970,"pages":{"first":8510,"last":8511},"keywords":["DC: Data Mining","DC: Knowledge Representation and Reasoning","DC: Machine Learning","DC: Search"],"videos":[],"references":[{"position":1,"raw":"[Akoglu et al., 2015] Leman Akoglu, Hanghang Tong, and Danai Koutra. 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IEEE Trans. Knowl. Data Eng., 31(10):1849-1862, 2019.","title":"A nonparametric approach to uncovering connected anomalies by tree shaped priors","authors":"Nannan Wu, Feng Chen, Jianxin Li, Jinpeng Huai, Baojian Zhou, Bo Li, Naren Ramakrishnan","year":"2019","venue":"IEEE Trans. Knowl. Data Eng","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Zhang and Zhao, 2022] Zheng Zhang and Liang Zhao. Un- supervised deep subgraph anomaly detection. In 2022 IEEE International Conference on Data Mining (ICDM), pages 753-762, 2022.","title":"Unsupervised deep subgraph anomaly detection","authors":"Zheng Zhang, Liang Zhao","year":"2022","venue":"2022 IEEE International Conference on Data Mining (ICDM)","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}