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Graph-structured data arise naturally in many different application domains.
Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks. In Proc. of KDD . 1903–1911
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Internet: Diameter of the World-Wide Web
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Learning to Forget: Continual Prediction with LSTM
Felix A. Gers, Jurgen Schmidhuber, and Fred A. Cummins. 2000 · 2000
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Community structure in social and biological networks
M. Girvan and M. E. J. Newman. 2002 · 2002
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The link prediction problem for social networks. In Proc. of CIKM . 556–559
David Liben-Nowell and Jon Kleinberg. 2003 · 2003
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Ecological subsystems via graph theory: the role of strongly connected components
Stefano Allesina, Antonio Bodini, and Cristina Bondavalli. 2005 · 2005
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On Mining Cross-Graph Quasi-Cliques. In Proc. of KDD . 228–238
Jian Pei, Daxin Jiang, and Aidong Zhang. 2005 · 2005
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Sampling from large graphs. In Proc. of KDD . 631–636
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Transferring Naive Bayes Classifiers for Text Classification. In Proc. of AAAI . 540–545
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Graph Data Management and Mining: A Survey of Algorithms and Applications . Advances in Database Systems, Vol. 40
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Supervised random walks: predicting and recommending links in social networks. In Proc. of WSDM . 635–644
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Networks in Plant Epidemiology: From Genes to Landscapes, Countries, and Continents
Mathieu Moslonka-Lefebvre, Ann Finley, Ilaria Dorigatti, Katharina Dehnen-Schmutz, Tom Harwood, Michael J. Jeger, Xiangming Xu, Ottmar Holdenrieder, and Marco Pautasso. 2011 · 2011
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Weisfeiler-Lehman Graph Kernels
Nino Shervashidze, Pascal Schweitzer, Erik Jan van Leeuwen, Kurt Mehlhorn, and Karsten M. Borgwardt. 2011 · 2011
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Co-author Relationship Prediction in Heterogeneous Bibliographic Networks. In Proc. of ASONAM . 121–128
Yizhou Sun, Rick Barber, Manish Gupta, Charu C. Aggarwal, and Jiawei Han. 2011 · 2011
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Heterogeneous Transfer Learning for Image Classification. In Proc. of AAAI . 1304–1309
Yin Zhu, Yuqiang Chen, Zhongqi Lu, Sinno Jialin Pan, Gui-Rong Xue, Yong Yu, and Qiang Yang. 2011 · 2011
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Link Prediction in a Modified Heterogeneous Bibliographic Network. In Proc. of ASONAM . 442–449
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Transfer Significant Subgraphs across Graph Databases. In Proc. of SDM . 552–563
Xiaoxiao Shi, Xiangnan Kong, and Philip S. Yu. 2012 · 2012
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Graph Classification: A Diversified Discriminative Feature Selection Approach. In Proc. of CIKM . 205–214
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A survey of frequent subgraph mining algorithms
Chuntao Jiang, Frans Coenen, and Michele Zito. 2013 · 2013
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Graph similarity search with edit distance constraint in large graph databases. In Proc. of CIKM . 1595–1600
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Network Sampling: From Static to Streaming Graphs
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Stability of influence maximization. In Proc. of KDD . 1256–1265
Xinran He and David Kempe. 2014 · 2014
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Recurrent Models of Visual Attention. In Proc. of NIPS . 2204–2212
Volodymyr Mnih, Nicolas Heess, Alex Graves, and Koray Kavukcuoglu. 2014 · 2014
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Learning and Transferring Mid-Level Image Representations using Convolutional Neural Networks. In Proc. of CVPR . 1717–1724
Maxime Oquab, Leon Bottou, Ivan Laptev, and Josef Sivic. 2014 · 2014
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DeepWalk: online learning of social representations. In Proc. of KDD . 701–710
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Sequence to Sequence Learning with Neural Networks. In Proc. of NIPS . 3104–3112
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Introduction to the Special Section on Urban Computing
Yu Zheng, Licia Capra, Ouri Wolfson, and Hai Yang. 2014 · 2014
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Graph based anomaly detection and description: a survey
On Deep Learning for Trust-Aware Recommendations in Social Networks
Shuiguang Deng, Longtao Huang, Guandong Xu, Xindong Wu, and Zhaohui Wu. 2017 · 2017
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metapath2vec: Scalable Representation Learning for Heterogeneous Networks. In Proc. of KDD . 135–144
Yuxiao Dong, Nitesh V Chawla, and Ananthram Swami. 2017 · 2017
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Inductive Representation Learning on Large Graphs. In Proc. of NIPS . 1–11
Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017 · 2017
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Semi-supervised classification with graph convolutional networks. In Proc. of ICLR . 1–14
Thomas N Kipf and Max Welling. 2017 · 2017
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Identifying Deep Contrasting Networks from Time Series Data: Application to Brain Network Analysis. In Proc. of SDM . 543–551
John Boaz Lee, Xiangnan Kong, Yihan Bao, and Constance Moore. 2017 · 2017
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Leman Akoglu, Hanghang Tong, and Danai Koutra. 2015 · 2015
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Neural Machine Translation by Jointly Learning to Align and Translate. In Proc. of ICLR . 1–15
Dzmitry Bahdanau, KyungHyun Cho, and Yoshua Bengio. 2015 · 2015
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Convolutional Networks on Graphs for Learning Molecular Fingerprints. In Proc. of NIPS . 2224–2232
David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gomez-Bombarelli, Timothy Hirzel, Alan Aspuru-Guzik, and Ryan P. Adams. 2015 · 2015
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Link Mining: A Survey
Lise Getoor and Christopher P. Diehl. 2015 · 2015
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Effective Approaches to Attention-based Neural Machine Translation. In Proc. of EMNLP . 1412–1421
Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015
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Role Discovery in Networks
Ryan A. Rossi and Nesreen K. Ahmed. 2015 · 2015
Cited alongside, same era.
LINE: Large-scale Information Network Embedding. In Proc. of WWW . 1067–1077
Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, and Qiaozhu Mei. 2015 · 2015
Cited alongside, same era.
An Influence Propagation View of PageRank
Qi Liu, Biao Xiang, Nicholas Jing Yuan, Enhong Chen, Hui Xiong, Yi Zheng, and Yu Yang. 2017 · 2017
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A Survey of Heterogeneous Information Network Analysis
Chuan Shi, Yitong Li, Jiawei Zhang, Yizhou Sun, and Philip S. Yu. 2017 · 2017
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Link Prediction via Ranking Metric Dual-level Attention Network Learning. In Proc. of IJCAI . 3525–3531
Zhou Zhao, Ben Gao, Vicent W. Zheng, Deng Cai, Xiaofei He, and Yueting Zhuang. 2017 · 2017
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Learning Role-based Graph Embeddings. In arXiv:1802.02896
Nesreen K Ahmed, Ryan Rossi, John Boaz Lee, Xiangnan Kong, Theodore L Willke, Rong Zhou, and Hoda Eldardiry. 2018 · 2018
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A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications
HongYun Cai, Vincent W. Zheng, and Kevin Chen-Chuan Chang. 2018 · 2018
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Stochastic Training of Graph Convolutional Networks with Variance Reduction. In arXiv:1710.10568v3
Jianfei Chen, Jun Zhu, and Le Song. 2018 · 2018
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SPINE: Structural Identity Preserved Inductive Network Embedding. In arXiv:1802.03984v1
Junliang Guo, Linli Xu, and Enhong Cheng. 2018 · 2018
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Neural Knowledge Acquisition via Mutual Attention Between Knowledge Graph and Text. In Proc. of AAAI . 1–8
Xu Han, Zhiyuan Liu, and Maosong Sun. 2018 · 2018
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Graph Classification using Structural Attention. In Proc. of KDD . 1–9
John Boaz Lee, Ryan Rossi, and Xiangnan Kong. 2018 · 2018
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Seongok Ryu, Jaechang Lim, and Woo Youn Kim. 2018 · 2018
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Edge Attention-based Multi-Relational Graph Convolutional Networks. In arXiv:1802.04944v1
Chao Shang, Qinqing Liu, Ko-Shin Chen, Jiangwen Sun, Jin Lu, Jinfeng Yi, and Jinbo Bi. 2018 · 2018
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Attention-based Graph Neural Network for Semi-supervised Learning. In arXiv:1803.03735v1
Kiran K. Thekumparampil, Chong Wang, Sewoong Oh, and Li-Jia Li. 2018 · 2018
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Graph Attention Networks. In Proc. of ICLR . 1–12
Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2018 · 2018
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Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks. In arXiv:1804.00823v3
Kun Xu, Lingfei Wu, Zhiguo Wang, Yansong Feng, Michael Witbrock, and Vadim Sheinin. 2018 · 2018
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Commonsense Knowledge Aware Conversation Generation with Graph Attention. In Proc. of IJCAI-ECAI . 1–7
Hao Zhou, Tom Yang, Minlie Huang, Haizhou Zhao, Jingfang Xu, and Xiaoyan Zhu. 2018 · 2018
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Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. In Proc. of ICML . 2048–2057
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, and Yoshua Bengio. 2015 · 2057
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