58 citations · 120 across the 7 of their papers we have counts for
7 papers
Temporal Graph Representation Learning with Adaptive Augmentation Contrastive
Hongjiang Chen, Pengfei Jiao, Huijun Tang +1
Temporal graph representation learning aims to generate low-dimensional dynamic node embeddings to capture temporal information as well as structural and property information. Curr…
Representation Learning on Heterostructures via Heterogeneous Anonymous Walks
Xuan Guo, Pengfei Jiao, Ting Pan +4
Capturing structural similarity has been a hot topic in the field of network embedding recently due to its great help in understanding the node functions and behaviors. However, ex…
Block Modeling-Guided Graph Convolutional Neural Networks
Dongxiao He, Chundong Liang, Huixin Liu +3
Graph Convolutional Network (GCN) has shown remarkable potential of exploring graph representation. However, the GCN aggregating mechanism fails to generalize to networks with hete…
Analysis of 5G academic Network based on graph representation learning method
Xiaoming Li, Guangquan Xu, Wei Yu +2
With the rapid development of 5th Generation Mobile Communication Technology (5G), the diverse forms of collaboration and extensive data in academic social networks constructed by…
A Survey on Role-Oriented Network Embedding
Pengfei Jiao, Xuan Guo, Ting Pan +2
Recently, Network Embedding (NE) has become one of the most attractive research topics in machine learning and data mining. NE approaches have achieved promising performance in var…
A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning
Di Jin, Zhizhi Yu, Pengfei Jiao +5
Community detection, a fundamental task for network analysis, aims to partition a network into multiple sub-structures to help reveal their latent functions. Community detection ha…
NRPA: Neural Recommendation with Personalized Attention
Hongtao Liu, Fangzhao Wu, Wenjun Wang +4
Existing review-based recommendation methods usually use the same model to learn the representations of all users/items from reviews posted by users towards items. However, differe…