Frequent principal fault detection and localization (FPFDL), as a new problem of fault
diagnosis of the wind turbine system in practice, has gained a growing concern in wind …

Network embedding (NE), also known as network representation learning (NRL), is a
method to learn a low-dimensional latent representation of nodes in an information network …

There are multiple types of information networks, including: social networks, citation
networks, email communications networks, etc. are becoming popular in recent years. They …

Sentiment analysis of the text deals with the mining of the opinions of people from their
written communication. With the increasing usage of online social media platforms for user …

The extraction of valuable insights from unstructured content has attracted much attention in
the last decades. Main results lie in the area of text mining, while the understanding of …

Most of the existing hypernetwork representation learning methods fail to fully consider the
hyperedges, leading to the untapped potential of information contained within the …

Network alignment, which is also known as user identity linkage, is a kind of network
analysis task that predicts overlapping users between two different social networks. This …

The accurate prediction of solar X-ray flux is a difficult problem due to noise and
miscalibration of sensors, missing data, and the effects of the Earth's position relative to the …

图卷积网络(GCN) 能够适应不同结构的图, 但多数基于GCN 的方法难以有效地捕获网络的高阶
相似性. 简单添加卷积层将导致输出特征过度平滑并使它们难以区分, 而且深层神经网络更难 …

Heterogeneous information networks are widely used to represent real world applications in
forms of social networks, word co-occurrence networks, and communication networks, etc …