Topic-aware heterogeneous graph neural network for link prediction

Topic-aware heterogeneous graph neural network for link prediction

Heterogeneous graphs (HGs), consisting of multiple types of nodes and links, can characterize a variety of real-world complex systems. Recently, heterogeneous graph neural networks (HGNNs), as a powerful graph embedding method to aggregate heterogeneous structure and attribute information, has earne...

Saved in:

書目詳細資料
Main Authors:	XU, Siyong, YANG, Cheng, FANG, Yuan, TIANCHI, Yang, ZHANG, Luhao
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2021
主題:	Heterogeneous graph Graph neural networks Representation learning Link prediction Databases and Information Systems
在線閱讀:	https://ink.library.smu.edu.sg/sis_research/6805 https://ink.library.smu.edu.sg/context/sis_research/article/7808/viewcontent/123.pdf
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

相似書籍

Link prediction on latent heterogeneous graphs
由: NGUYEN, Trung Kien, et al.
出版: (2023)

Learning on heterogeneous graphs using high-order relations
由: Lee, See Hian, et al.
出版: (2021)

Heterogeneous graph neural network with multi-view representation learning
由: SHAO, Zezhi, et al.
出版: (2023)

Metagraph-based learning on heterogeneous graphs
由: FANG, Yuan, et al.
出版: (2019)

Dynamic heterogeneous graph embedding via heterogeneous Hawkes process
由: JI, Yugang, et al.
出版: (2021)

The 4th workshop on heterogeneous information network analysis and applications (HENA 2021)
由: SHI, Chuan, et al.
出版: (2021)

Diffusion-based negative sampling on graphs for link prediction
由: FANG, Yuan, et al.
出版: (2024)

Dynamic meta-path guided temporal heterogeneous graph neural networks
由: JI, Yugang, et al.
出版: (2024)

TOWARD EFFECTIVE NEURAL NETWORKS ON GRAPH DATA
由: WANG YIWEI
出版: (2023)

Motif graph neural network
由: CHEN, Xuexin, et al.
出版: (2023)

Contrastive pre-training of GNNs on heterogeneous graphs
由: JIANG, Xunqiang, et al.
出版: (2021)

GRAPH EMBEDDINGS FOR LINK PREDICTION IN SCIENTIFIC COLLABORATION NETWORKS
由: LAI YI
出版: (2021)

A class-aware representation refinement framework for graph classification
由: Xu, Jiaxing, et al.
出版: (2024)

Pre-training on large-scale heterogeneous graph
由: JIANG, Xunqiang, et al.
出版: (2021)

Harnessing collective structure knowledge in data augmentation for graph neural networks
由: MA, Rongrong, et al.
出版: (2024)

On the feasibility of Simple Transformer for dynamic graph modeling
由: WU, Yuxia, et al.
出版: (2024)

Heterogeneous graph transformer with poly-tokenization
由: LU, Zhiyuan, et al.
出版: (2024)

ADVANCING GRAPH NEURAL NETWORKS WITH HL-HGAT: A HODGE-LAPLACIAN AND ATTENTION MECHANISM APPROACH FOR HETEROGENEOUS GRAPH-STRUCTURED DATA
由: HUANG JINGHAN
出版: (2024)

Masked autoencoders for contrastive learning of heterogenous graphs
由: Srinthi Nachiyar D/O Thangamuthu
出版: (2024)

LORA: Link obfuscation by randomization in graphs
由: Xiao, Q., et al.
出版: (2013)

When convolutional network meets temporal heterogeneous graphs: an effective community detection method
由: Zheng, Yaping, et al.
出版: (2023)

Deep learning for graph structured data
由: Dwivedi Vijay Prakash
出版: (2024)

MANDO-GURU: vulnerability detection for smart contract source code by heterogeneous graph embeddings
由: NGUYEN, Huu Hoang, et al.
出版: (2022)

Probabilistic Logic Graph Attention Networks for Reasoning.
由: Vardhan, L Vivek Harsha, et al.
出版: (2020)

TOWARD EFFECTIVE AND EFFICIENT GRAPH NEURAL NETWORKS WITH IMPLICIT LAYERS
由: LIU JUNCHENG
出版: (2024)

MANDO: Multi-level heterogeneous graph embeddings for fine-grained detection of smart contract vulnerabilities
由: NGUYEN, Huu Hoang, et al.
出版: (2022)

Learning to count isomorphisms with graph neural networks
由: YU, Xingtong, et al.
出版: (2023)

Accelerating large-scale heterogeneous interaction graph embedding learning via importance sampling
由: JI, Yugang, et al.
出版: (2021)

Generalizing graph neural network across graphs and time
由: WEN, Zhihao
出版: (2023)

Neighbor-anchoring adversarial graph neural networks
由: LIU, Zemin, et al.
出版: (2023)

Douban books score prediction based on graph neural network and BERT
由: Cao, Yuchen
出版: (2025)

Towards effective graph representations by leveraging geometric concepts
由: Lee, See Hian
出版: (2024)

Joint hyperbolic and Euclidean geometry contrastive graph neural networks
由: XU, Xiaoyu, et al.
出版: (2022)

LEARNING ON GRAPHS
由: FENG FULI
出版: (2019)

Node-wise localization of graph neural networks
由: LIU, Zemin, et al.
出版: (2021)

HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation
由: DU, Yuntao, et al.
出版: (2022)

Variational graph author topic modeling
由: ZHANG, Ce, et al.
出版: (2022)

Graph contrastive learning with stable and scalable spectral encoding
由: BO, Deyu, et al.
出版: (2023)

Confidence-aware graph regularization with heterogeneous pairwise features
由: FANG, Yuan, et al.
出版: (2012)

Learning to pre-train graph neural networks
由: LU, Yuanfu, et al.
出版: (2021)