Complex Network Analysis using Artificial Intelligence Algorithms

被引：0
|
作者：
Chira, Camelia [1 ]
机构：
[1] Babes Bolyai Univ, Dept Comp Sci, Cluj Napoca, Romania
来源：
2022 24TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING, SYNASC | 2022年
关键词：
Artificial Intelligence; Complex Networks;
D O I：
10.1109/SYNASC57785.2022.00010
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Network science is emerging as a vibrant research field with important applications in finance, biology, chemistry, physics, engineering and health. This short paper presents an overview of some challenging tasks related to the analysis of complex networks, including community detection, discovery of cycles and identification of important nodes. The solutions proposed for these important network analysis tasks engage Artificial Intelligence models and are briefly presented with an emphasis on their performance as well as the main related research questions. The analysis of financial networks is also discussed, showing the potential of using network science tools to discover financial cycles and paths.
引用
收藏
页码：9 / 11
页数：3
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