THGNN: An Embedding-based Model for Anomaly Detection in Dynamic Heterogeneous Social Networks-Reference-Cited by-同舟云学术

THGNN: An Embedding-based Model for Anomaly Detection in Dynamic Heterogeneous Social Networks

Published:2023-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
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Author:

Li Yilin¹^ORCID,Zhu Jiaqi¹^ORCID,Zhang Congcong¹^ORCID,Yang Yi²^ORCID,Zhang Jiawen³^ORCID,Qiao Ying²^ORCID,Wang Hongan²^ORCID

Affiliation:

1. Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China

2. Institute of Software, Chinese Academy of Sciences, Beijing, China

3. The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

Funder

CAS Project for Young Scientists in Basic Research

Strategic Priority Research Program of Chinese Academy of Sciences

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583780.3615079

Reference61 articles.

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4. Claudio D. T. Barros , Matheus R. F. Mendoncc a , Alex B. Vieira, and Artur Ziviani. 2023 . A Survey on Embedding Dynamic Graphs. Comput. Surveys , Vol. 55 , 2 (2023), 10:1--10:37. Claudio D. T. Barros, Matheus R. F. Mendoncc a, Alex B. Vieira, and Artur Ziviani. 2023. A Survey on Embedding Dynamic Graphs. Comput. Surveys, Vol. 55, 2 (2023), 10:1--10:37.

5. Patient Subtyping via Time-Aware LSTM Networks