With the widespread use of information technologies, information networks are becoming
increasingly popular to capture complex relationships across various disciplines, such as …

Heterogeneous information networks usually contain different kinds of nodes and
distinguishing types of relations, which can preserve more information than homogeneous …

Network embedding, aiming to embed a network into a low dimensional vector space while
preserving the inherent structural properties of the network, has attracted considerable …

实际系统往往由大量类型各异, 彼此交互的组件构成. 目前, 大多数工作将这些交互系统建模为同
质信息网络, 并未考虑不同类型对象的复杂异质交互关系, 因而造成大量信息损失. 近年来 …

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 …

Diversity is a concept relevant to numerous domains of research varying from ecology, to
information theory, and to economics, to cite a few. It is a notion that is steadily gaining …

With the increasing popularity of graph structures, Graph embedding, Which aims to project
nodes into low dimensional space while preserving the topological structure information of …

Most existing heterogeneous graph neural network models need more effective integration
and full exploitation of features at different network levels to prevent overfitting. To address …

Regularities of prescriptions are important for both clinical practice and novel healthcare
development in clinical traditional Chinese medicine (TCM). To address this issue and meet …

The available spatial data are rapidly growing and also diversifying. One may obtain in large
quantities information such as annotated point/place of interest (POIs), check-in comments …