Y Xie, B Yu, S Lv, C Zhang, G Wang, M Gong - Pattern recognition, 2021 - Elsevier
Heterogeneous information networks usually contain different kinds of nodes and distinguishing types of relations, which can preserve more information than homogeneous …
D Zhu, P Cui, Z Zhang, J Pei… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
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 …
N Tong, Y Tang, B Chen, L Xiong - Expert Systems with Applications, 2021 - Elsevier
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 …
X Dong, Y Zhang, K Pang, F Chen, M Lu - Knowledge-Based Systems, 2022 - Elsevier
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 …
K Feng, G Rao, L Zhang, Q Cong - Applied Intelligence, 2023 - Springer
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 …
C Ruan, Y Wang, Y Zhang, Y Yang - International Conference on …, 2019 - Springer
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 …