Abstract Knowledge Graph (KG) provides high-quality structured knowledge for various
downstream knowledge-aware tasks (such as recommendation and intelligent question …

Social network analysis (SNA) is a core pursuit of analyzing social networks today. In
addition to the usual statistical techniques of data analysis, these networks are investigated …

Networks evolve continuously over time with the addition, deletion, and changing of links
and nodes. Although many networks contain this type of temporal information, the majority of …

近年来, 真实网络中小世界效应和无标度特性的发现激起了物理学界对复杂网路的研究热潮.
复杂网络区别于以前广泛研究的规则网络和随机网络最重要的统计特征是什么 …

The Gaussian mechanism is an essential building block used in multitude of differentially
private data analysis algorithms. In this paper we revisit the Gaussian mechanism and show …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Emerging graph neural networks (GNNs) have extended the successes of deep learning
techniques against datasets like images and texts to more complex graph-structured data …

From social networks such as Facebook, the World Wide Web and the Internet, to the
complex interactions between proteins in the cells of our bodies, we constantly face the …

Exactly half a century has passed since the launch of the first documented research project
(1965 Dendral) on computer‐assisted organic synthesis. Many more programs were created …

Traditionally distributed graph processing systems have largely focused on scalability
through the optimizations of inter-node communication and load balance. However, they …