4.7 Article

L-BGNN: Layerwise Trained Bipartite Graph Neural Networks

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

A Comprehensive Survey on Graph Neural Networks

Zonghan Wu et al.

Summary: This article provides a comprehensive overview of graph neural networks (GNNs) in data mining and machine learning fields. It discusses the taxonomy of GNNs, their applications, and summarizes open-source codes, benchmark data sets, and model evaluation. The article also proposes potential research directions in this rapidly growing field.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2021)

Article Computer Science, Information Systems

Large-Scale Question Tagging via Joint Question-Topic Embedding Learning

Liqiang Nie et al.

ACM TRANSACTIONS ON INFORMATION SYSTEMS (2020)

Proceedings Paper Computer Science, Information Systems

BiANE: Bipartite Attributed Network Embedding

Wentao Huang et al.

PROCEEDINGS OF THE 43RD INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR '20) (2020)

Proceedings Paper Computer Science, Artificial Intelligence

L2-GCN Layer-Wise and Learned Efficient Training of Graph Convolutional Networks

Yuning You et al.

2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2020)

Proceedings Paper Computer Science, Artificial Intelligence

Label Efficient Semi-Supervised Learning via Graph Filtering

Qimai Li et al.

2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019) (2019)

Proceedings Paper Computer Science, Information Systems

Heterogeneous Graph Neural Network

Chuxu Zhang et al.

KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING (2019)

Proceedings Paper Computer Science, Information Systems

Adversarial Learning on Heterogeneous Information Networks

Binbin Hu et al.

KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING (2019)

Proceedings Paper Computer Science, Information Systems

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

Wei-Lin Chiang et al.

KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING (2019)

Proceedings Paper Computer Science, Theory & Methods

Heterogeneous Graph Attention Network

Xiao Wang et al.

WEB CONFERENCE 2019: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW 2019) (2019)

Proceedings Paper Computer Science, Artificial Intelligence

SHNE: Representation Learning for Semantic-Associated Heterogeneous Networks

Chuxu Zhang et al.

PROCEEDINGS OF THE TWELFTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING (WSDM'19) (2019)

Proceedings Paper Computer Science, Information Systems

BiNE: Bipartite Network Embedding

Ming Gao et al.

ACM/SIGIR PROCEEDINGS 2018 (2018)

Proceedings Paper Computer Science, Information Systems

Local and Global Information Fusion for Top-N Recommendation in Heterogeneous Information Network

Binbin Hu et al.

CIKM'18: PROCEEDINGS OF THE 27TH ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT (2018)

Proceedings Paper Computer Science, Artificial Intelligence

DeepInf: Social Influence Prediction with Deep Learning

Jiezhong Qiu et al.

KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING (2018)

Proceedings Paper Computer Science, Artificial Intelligence

Leveraging Meta-path based Context for Top-N Recommendation with A Neural Co-Attention Model

Binbin Hu et al.

KDD'18: PROCEEDINGS OF THE 24TH ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING (2018)

Proceedings Paper Computer Science, Information Systems

HIN2Vec: Explore Meta-paths in Heterogeneous Information Networks for Representation Learning

Tao-yang Fu et al.

CIKM'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT (2017)

Proceedings Paper Computer Science, Information Systems

Neural Collaborative Filtering

Xiangnan He et al.

PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB (WWW'17) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

metapath2vec: Scalable Representation Learning for Heterogeneous Networks

Yuxiao Dong et al.

KDD'17: PROCEEDINGS OF THE 23RD ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (2017)

Article Computer Science, Hardware & Architecture

MATRIX FACTORIZATION TECHNIQUES FOR RECOMMENDER SYSTEMS

Yehuda Koren et al.

COMPUTER (2009)

Article Computer Science, Artificial Intelligence

The Graph Neural Network Model

Franco Scarselli et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2009)

Article Computer Science, Software Engineering

Amazon.com recommendation - Item-to-item collaborative filtering

G Linden et al.

IEEE INTERNET COMPUTING (2003)