ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1806.01973
  4. Cited By
Graph Convolutional Neural Networks for Web-Scale Recommender Systems

Graph Convolutional Neural Networks for Web-Scale Recommender Systems

6 June 2018
Rex Ying
Ruining He
Kaifeng Chen
Pong Eksombatchai
William L. Hamilton
J. Leskovec
    GNNBDL
ArXiv (abs)PDFHTML

Papers citing "Graph Convolutional Neural Networks for Web-Scale Recommender Systems"

50 / 1,342 papers shown
Title
Revisiting Graph based Collaborative Filtering: A Linear Residual Graph
  Convolutional Network Approach
Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network ApproachAAAI Conference on Artificial Intelligence (AAAI), 2020
Lei Chen
Le Wu
Richang Hong
Kun Zhang
Meng Wang
GNN
219
585
0
28 Jan 2020
Efficient and Stable Graph Scattering Transforms via Pruning
Efficient and Stable Graph Scattering Transforms via PruningIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
V. Ioannidis
Siheng Chen
G. Giannakis
150
13
0
27 Jan 2020
TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced
  Graph Neural Network
TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural NetworkThe Web Conference (WWW), 2020
Jiaming Shen
Zhihong Shen
Chenyan Xiong
Chi Wang
Kuansan Wang
Jiawei Han
188
80
0
26 Jan 2020
Linking Bank Clients using Graph Neural Networks Powered by Rich
  Transactional Data
Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional DataInternational Journal of Data Science and Analysis (JDSA), 2020
Valentina Shumovskaia
Kirill Fedyanin
I. Sukharev
Dmitry Berestnev
Maxim Panov
129
30
0
23 Jan 2020
Physical-Virtual Collaboration Modeling for Intra-and Inter-Station
  Metro Ridership Prediction
Physical-Virtual Collaboration Modeling for Intra-and Inter-Station Metro Ridership Prediction
Lingbo Liu
Jingwen Chen
Hefeng Wu
Jiajie Zhen
Guanbin Li
Liang Lin
126
11
0
14 Jan 2020
BasConv: Aggregating Heterogeneous Interactions for Basket
  Recommendation with Graph Convolutional Neural Network
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural NetworkSDM (SDM), 2020
Zhiwei Liu
Mengting Wan
Stephen D. Guo
Kannan Achan
Philip S. Yu
194
72
0
14 Jan 2020
HyGCN: A GCN Accelerator with Hybrid Architecture
HyGCN: A GCN Accelerator with Hybrid ArchitectureInternational Symposium on High-Performance Computer Architecture (HPCA), 2020
Yurui Lai
Lei Deng
Xing Hu
Ling Liang
Yujing Feng
Xiaochun Ye
Zhimin Zhang
Xiaochun Ye
Yuan Xie
GNN
219
327
0
07 Jan 2020
GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms
GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous PlatformsSymposium on Field Programmable Gate Arrays (FPGA), 2019
Hanqing Zeng
Viktor Prasanna
GNN
125
135
0
31 Dec 2019
A Gentle Introduction to Deep Learning for Graphs
A Gentle Introduction to Deep Learning for GraphsNeural Networks (NN), 2019
D. Bacciu
Federico Errica
Alessio Micheli
Marco Podda
AI4CEGNN
235
302
0
29 Dec 2019
Solving Cold Start Problem in Recommendation with Attribute Graph Neural
  Networks
Solving Cold Start Problem in Recommendation with Attribute Graph Neural Networks
T. Qian
Yile Liang
Qing Li
CML
156
11
0
28 Dec 2019
Unsupervised Learning of Graph Hierarchical Abstractions with
  Differentiable Coarsening and Optimal Transport
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal TransportAAAI Conference on Artificial Intelligence (AAAI), 2019
Tengfei Ma
Jie Chen
143
26
0
24 Dec 2019
Expanding Label Sets for Graph Convolutional Networks
Expanding Label Sets for Graph Convolutional Networks
Mustafa Coşkun
Burcu Bakir-Gungor
Mehmet Koyutürk
GNN
59
2
0
18 Dec 2019
ragamAI: A Network Based Recommender System to Arrange a Indian
  Classical Music Concert
ragamAI: A Network Based Recommender System to Arrange a Indian Classical Music ConcertInternational Conference on Machine Learning and Applications (ICMLA), 2019
A. Bagavathi
S. Krishnan
Sanjay Subrahmanyan
Narasimhan S. L.
98
0
0
08 Dec 2019
Hyperbolic Graph Attention Network
Hyperbolic Graph Attention NetworkIEEE Transactions on Big Data (IEEE Trans. Big Data), 2019
Yiding Zhang
Tianlin Li
Xunqiang Jiang
C. Shi
Yanfang Ye
GNN
154
150
0
06 Dec 2019
Fine-Grained Emotion Classification of Chinese Microblogs Based on Graph
  Convolution Networks
Fine-Grained Emotion Classification of Chinese Microblogs Based on Graph Convolution NetworksWorld wide web (Bussum) (WWW), 2019
Yu-Chen Lai
Linfeng Zhang
Donghong Han
Rui Zhou
Guoren Wang
98
66
0
05 Dec 2019
On model selection for scalable time series forecasting in transport
  networks
On model selection for scalable time series forecasting in transport networks
Julien Monteil
Anton Dekusar
Claudio Gambella
Y. Lassoued
M. Mevissen
AI4TS
68
2
0
29 Nov 2019
SWAG: Item Recommendations using Convolutions on Weighted Graphs
SWAG: Item Recommendations using Convolutions on Weighted Graphs
Amit Pande
Kai Ni
Venkataramani Kini
GNN
89
10
0
22 Nov 2019
An End-to-End Framework for Cold Question Routing in Community Question
  Answering Services
An End-to-End Framework for Cold Question Routing in Community Question Answering ServicesInternational Joint Conference on Artificial Intelligence (IJCAI), 2019
Jiankai Sun
Jie Zhao
Huan Sun
Srinivasan Parthasarathy
135
30
0
22 Nov 2019
Graph Pruning for Model Compression
Graph Pruning for Model Compression
Mingyang Zhang
Xinyi Yu
Jingtao Rong
L. Ou
GNN
144
9
0
22 Nov 2019
GraLSP: Graph Neural Networks with Local Structural Patterns
GraLSP: Graph Neural Networks with Local Structural PatternsAAAI Conference on Artificial Intelligence (AAAI), 2019
Yilun Jin
Guojie Song
C. Shi
162
54
0
18 Nov 2019
Layer-Dependent Importance Sampling for Training Deep and Large Graph
  Convolutional Networks
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional NetworksNeural Information Processing Systems (NeurIPS), 2019
Difan Zou
Ziniu Hu
Yewen Wang
Song Jiang
Luke Huan
Quanquan Gu
GNN
236
319
0
17 Nov 2019
Graph-Revised Convolutional Network
Graph-Revised Convolutional Network
Donghan Yu
Ruohong Zhang
Zhengbao Jiang
Yuexin Wu
Yiming Yang
GNN
362
104
0
17 Nov 2019
Hierarchical Graph Pooling with Structure Learning
Hierarchical Graph Pooling with Structure LearningAAAI Conference on Artificial Intelligence (AAAI), 2019
Zhen Zhang
Jiajun Bu
Martin Ester
Jianfeng Zhang
Chengwei Yao
Zhi Yu
Can Wang
235
197
0
14 Nov 2019
A Capsule Network-based Model for Learning Node Embeddings
A Capsule Network-based Model for Learning Node EmbeddingsInternational Conference on Information and Knowledge Management (CIKM), 2019
Dai Quoc Nguyen
T. Nguyen
Dat Quoc Nguyen
Dinh Q. Phung
GNN
131
11
0
12 Nov 2019
GraphDefense: Towards Robust Graph Convolutional Networks
GraphDefense: Towards Robust Graph Convolutional Networks
Xiaoyun Wang
Xuanqing Liu
Cho-Jui Hsieh
OODAAMLGNN
204
36
0
11 Nov 2019
HighwayGraph: Modelling Long-distance Node Relations for Improving
  General Graph Neural Network
HighwayGraph: Modelling Long-distance Node Relations for Improving General Graph Neural Network
Deli Chen
Xiaoqian Liu
Yankai Lin
Peng Li
Jie Zhou
Qi Su
Xu Sun
GNN
133
2
0
10 Nov 2019
Graph Convolutional Networks Meet with High Dimensionality Reduction
Graph Convolutional Networks Meet with High Dimensionality Reduction
Mustafa Coşkun
GNNBDL
60
3
0
07 Nov 2019
Graph Transformer Networks
Graph Transformer NetworksNeural Information Processing Systems (NeurIPS), 2019
Seongjun Yun
Minbyul Jeong
Raehyun Kim
Jaewoo Kang
Hyunwoo J. Kim
486
1,190
0
06 Nov 2019
Certifiable Robustness to Graph Perturbations
Certifiable Robustness to Graph PerturbationsNeural Information Processing Systems (NeurIPS), 2019
Aleksandar Bojchevski
Stephan Günnemann
AAML
229
141
0
31 Oct 2019
Hyperbolic Graph Convolutional Neural Networks
Hyperbolic Graph Convolutional Neural NetworksNeural Information Processing Systems (NeurIPS), 2019
Ines Chami
Rex Ying
Christopher Ré
J. Leskovec
GNN
378
751
0
28 Oct 2019
Extreme Classification in Log Memory using Count-Min Sketch: A Case
  Study of Amazon Search with 50M Products
Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M ProductsNeural Information Processing Systems (NeurIPS), 2019
Tharun Medini
Qixuan Huang
Yiqiu Wang
Vijai Mohan
Anshumali Shrivastava
175
72
0
28 Oct 2019
Hyperbolic Graph Neural Networks
Hyperbolic Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2019
Qi Liu
Maximilian Nickel
Douwe Kiela
AI4CEGNN
209
430
0
28 Oct 2019
Diffusion Improves Graph Learning
Diffusion Improves Graph LearningNeural Information Processing Systems (NeurIPS), 2019
Johannes Klicpera
Stefan Weißenberger
Stephan Günnemann
GNN
907
814
0
28 Oct 2019
Improving Graph Attention Networks with Large Margin-based Constraints
Improving Graph Attention Networks with Large Margin-based Constraints
Guangtao Wang
Rex Ying
Jing-ling Huang
J. Leskovec
177
90
0
25 Oct 2019
KRED: Knowledge-Aware Document Representation for News Recommendations
KRED: Knowledge-Aware Document Representation for News Recommendations
Danyang Liu
Jianxun Lian
Shiyin Wang
Ying Qiao
Jiun-Hung Chen
Guangzhong Sun
Xing Xie
159
1
0
25 Oct 2019
Selective Attention Based Graph Convolutional Networks for Aspect-Level
  Sentiment Classification
Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classification
Xiaochen Hou
Jing Huang
Guangtao Wang
Xiaodong He
Bowen Zhou
224
60
0
24 Oct 2019
Predicting origin-destination ride-sourcing demand with a
  spatio-temporal encoder-decoder residual multi-graph convolutional network
Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional networkTransportation Research Part C: Emerging Technologies (TRC), 2019
Jintao Ke
Xiaoran Qin
Hai Yang
Zhengfei Zheng
Zheng Zhu
Jieping Ye
AI4TS
113
177
0
17 Oct 2019
DeepGCNs: Making GCNs Go as Deep as CNNs
DeepGCNs: Making GCNs Go as Deep as CNNsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
Ge Li
Matthias Muller
Guocheng Qian
Itzel C. Delgadillo
Abdulellah Abualshour
Ali K. Thabet
Guohao Li
3DPCGNN
222
193
0
15 Oct 2019
Characterizing Deep Learning Training Workloads on Alibaba-PAI
Characterizing Deep Learning Training Workloads on Alibaba-PAIIEEE International Symposium on Workload Characterization (IISWC), 2019
Mengdi Wang
Chen Meng
Guoping Long
Chuan Wu
Jun Yang
Jialin Li
Yangqing Jia
142
60
0
14 Oct 2019
Dynamic Embedding on Textual Networks via a Gaussian Process
Dynamic Embedding on Textual Networks via a Gaussian ProcessAAAI Conference on Artificial Intelligence (AAAI), 2019
Pengyu Cheng
Yitong Li
D. Ponsa
Liqun Cheng
David Carlson
Gary R. Bradski
94
10
0
05 Oct 2019
TransGCN:Coupling Transformation Assumptions with Graph Convolutional
  Networks for Link Prediction
TransGCN:Coupling Transformation Assumptions with Graph Convolutional Networks for Link PredictionInternational Conference on Knowledge Capture (K-CAP), 2019
Ling Cai
Bo Yan
Gengchen Mai
K. Janowicz
Rui Zhu
GNN
114
83
0
01 Oct 2019
Overlapping Community Detection with Graph Neural Networks
Overlapping Community Detection with Graph Neural Networks
Oleksandr Shchur
Stephan Günnemann
GNN
146
156
0
26 Sep 2019
Hyperspectral Image Classification With Context-Aware Dynamic Graph
  Convolutional Network
Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional NetworkIEEE Transactions on Geoscience and Remote Sensing (TGRS), 2019
Sheng Wan
Chen Gong
P. Zhong
Shirui Pan
Guangyu Li
Zhiqiang Wang
157
152
0
26 Sep 2019
MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training
  Unit
MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit
John Palowitch
Bryan Perozzi
121
22
0
25 Sep 2019
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph
  Neural Networks
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang
Da Zheng
Zihao Ye
Quan Gan
Mufei Li
...
Jiaqi Zhao
Haotong Zhang
Alex Smola
Jinyang Li
Zheng Zhang
AI4CEGNN
407
819
0
03 Sep 2019
Graph Representation Learning: A Survey
Graph Representation Learning: A SurveyAPSIPA Transactions on Signal and Information Processing (APSIPA TSIP), 2019
Fenxiao Chen
Yun Cheng Wang
Bin Wang
C.-C. Jay Kuo
GNNAI4TS
130
248
0
03 Sep 2019
AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload
  Rebalancing
AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing
Tong Geng
Ang Li
Runbin Shi
Chunshu Wu
Tianqi Wang
...
Pouya Haghi
Antonino Tumeo
Shuai Che
Steve Reinhardt
Martin C. Herbordt
GNN
450
8
0
23 Aug 2019
Spam Review Detection with Graph Convolutional Networks
Spam Review Detection with Graph Convolutional NetworksInternational Conference on Information and Knowledge Management (CIKM), 2019
Ao Li
Zhou Qin
Runshi Liu
Yiqun Yang
Dong Li
GNN
122
262
0
22 Aug 2019
Towards Knowledge-Based Recommender Dialog System
Towards Knowledge-Based Recommender Dialog SystemConference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Qibin Chen
Junyang Lin
Yichang Zhang
Ming Ding
Yukuo Cen
Hongxia Yang
Jie Tang
160
284
0
15 Aug 2019
GraphSW: a training protocol based on stage-wise training for GNN-based
  Recommender Model
GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model
Chang-You Tai
Meng-Ru Wu
Yun-Wei Chu
Shao-Yu Chu
85
3
0
13 Aug 2019
Previous
123...24252627
Next