Link prediction is the most basic and essential problem in complex networks. This study
analyzes the observed topological, time, attributive, label, weight, directional, and symbolic …

In this paper, we attempt to use the rating information to adjust linkage-weight between
nodes to improve effectiveness of product recommendation. As we all known, sometimes we …

Since the emergence of COVID-19, the number of infections has significantly increased. As
of April 7, 8: 00 am, the total number of global infections has already reached 1,338,415 …

Many of the real-world networks, such as complex social networks, are intrinsically weighted
networks, and therefore, traditional network models, such as binary network models, will …

摘要网络链接预测能够获取网络中丢失链接的重要信息或进行网络的动态演变分析.
现有的基于节点相似性的网络链接预测方法往往针对简单的一(多) 阶邻居信息或特定类型的 …

Identification of hidden relationships between domain attributes from different data sources
is of great practical significance and forms an emerging field in data mining. However …

Prediction is one of the typical applications in the research fields of machine learning and
data mining. Traditional predictive analytics focuses on estimating class membership or …

Aiming at the problem of event prediction in large-scale event network, a collapse subgraph
convolution (CSGCN) algorithm is proposed, which uses event subgraph to predict the …