Complex Network Analysis using Artificial Intelligence Algorithms

Camelia Chira
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Abstract

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.
使用人工智能算法的复杂网络分析
网络科学正在成为一个充满活力的研究领域,在金融、生物、化学、物理、工程和健康等领域有着重要的应用。这篇短文概述了与复杂网络分析相关的一些具有挑战性的任务,包括社区检测、循环发现和重要节点的识别。针对这些重要的网络分析任务提出的解决方案涉及人工智能模型,并简要介绍了它们的性能以及主要的相关研究问题。本文还讨论了金融网络的分析,展示了利用网络科学工具发现金融周期和路径的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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