IDGMS: a One-Stop Graph Mining System for Infectious Diseases
Paper
Paper/Presentation Title | IDGMS: a One-Stop Graph Mining System for Infectious Diseases |
---|---|
Presentation Type | Paper |
Authors | Xu, Zenghui, Yu, Ting, Hong, Xingyun, Li, Mingzhang, Zhang, Yang, Ren, Zujie and Zhang, Ji |
Journal or Proceedings Title | Proceedings of the 10th IEEE International Conference on Big Data (2022) |
Journal Citation | pp. 6835-6837 |
Number of Pages | 3 |
Year | 2023 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Place of Publication | United States |
Digital Object Identifier (DOI) | https://doi.org/10.1109/BigData55660.2022.10020537 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/10020537/ |
Web Address (URL) of Conference Proceedings | https://ieeexplore.ieee.org/xpl/conhome/10020192/proceeding |
Conference/Event | Proceedings of the 10th IEEE International Conference on Big Data (2022) |
Event Details | Proceedings of the 10th IEEE International Conference on Big Data (2022) Parent IEEE International Conference on Big Data Delivery In person Event Date 17 to end of 20 Dec 2022 Event Location Osaka, Japan |
Abstract | Data mining in infectious disease pandemic scenarios is a complex giant task involving data from various fields and requirements of real-time and dynamic. In this paper, we propose a graph mining system for the infectious disease pandemic, IDGMS, with one-stop, dynamic, and interactive characteristics. The system has been applied to solve problems from three view scales and performs well. The system is constructed as a loose coupling structure at the front and back ends and can be extended to more graph mining issues. To the best of our knowledge, we are the first graph system especially targeting data mining of infectious diseases. |
Keywords | infectious disease; graph mining system |
ANZSRC Field of Research 2020 | 460599. Data management and data science not elsewhere classified |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Zhejiang Lab, China |
South China University of Technology, China | |
University of Southern Queensland |
https://research.usq.edu.au/item/z5902/idgms-a-one-stop-graph-mining-system-for-infectious-diseases
51
total views1
total downloads1
views this month0
downloads this month