Collective Classification in Network Data

Cited by (1,004)

Items 901–1,000 of 1,004

1. Balancing structure and position information in Graph Transformer network with a learnable node embedding
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2. AGCL: Adaptive Graph Contrastive Learning for graph representation learning
   Jiajun Yu, Adele Lu Jia · 2023 · Neurocomputing
3. An Adaptive Learning Rate Deep Learning Optimizer Using Long and Short-Term Gradients Based on G–L Fractional-Order Derivative
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4. Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion
   Yuguang Yan, Yuanlin Chen, Shibo Wang, Hanrui Wu, Ruichu Cai · 2024 · Proceedings of the AAAI Conference on Artificial Intelligence
5. Graphusion: Latent Diffusion for Graph Generation
   Ling Qiang Yang, Zhilin Huang, Zhilong Zhang, Zhongyi Liu, Shenda Hong, Wentao Zhang, Wenming Yang, Bin Cui, Luxia Zhang · 2024 · IEEE Transactions on Knowledge and Data Engineering
6. Adaptive Neural Message Passing for Inductive Learning on Hypergraphs
   Devanshu Arya, Deepak Kumar Gupta, Stevan Rudinac, Marcel Worring · 2024 · IEEE Transactions on Pattern Analysis and Machine Intelligence
7. Active Inference for Collective Classification
   Mustafa Bilgic, Lise C. Getoor · 2010 · Proceedings of the AAAI Conference on Artificial Intelligence
8. Bipartite Edge Prediction via Transductive Learning over Product Graphs
   Hanxiao Liu, Yiming Yang · 2015
9. Link Prediction in Heterogeneous Collaboration Networks
   Xi Wang, Gita Sukthankar · 2014 · Lecture notes in social networks
10. Correcting evaluation bias of relational classifiers with network cross validation
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11. Exploit of online social networks with Semi-Supervised Learning
    Mingzhen Mo, Dingyan Wang, Baichuan Li, Dan Hong, Irwin King · 2010 · International Joint Conference on Neural Networks (IJCNN)
12. A citation-based approach to automatic topical indexing of scientific literature
    Abdulhussain E. Mahdi, Arash Joorabchi · 2010 · Journal of Information Science
13. User opinion classification in social media: A global consistency maximization approach
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14. Two‐order graph convolutional networks for semi‐supervised classification
    Sichao Fu, Weifeng Liu, Shuying Li, Yicong Zhou · 2019 · IET Image Processing
15. SPINE: Structural Identity Preserved Inductive Network Embedding
    Junliang Guo, Linli Xu, Jingchang Liu · 2019 · International Joint Conference on Artificial Intelligence
16. GNN-PIM: A Processing-in-Memory Architecture for Graph Neural Networks
    Zhao Wang, Yijin Guan, Guangyu Sun, Dimin Niu, Yuhao Wang, Hongzhong Zheng, Yinhe Han · 2020 · Communications in computer and information science
17. Beyond Localized Graph Neural Networks: An Attributed Motif Regularization Framework
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18. GraphPAS: Parallel Architecture Search for Graph Neural Networks
    Jiamin Chen, Jianliang Gao, Yibo Chen, Babatoundé Moctard Olouladé, Tengfei Lyu, Zhao Li · 2021 · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
19. Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks
    Binghui Wang, Jinyuan Jia, Neil Zhenqiang Gong · 2021 · Proceedings of the AAAI Conference on Artificial Intelligence
20. Orthogonal Over-Parameterized Training
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21. Walk Extraction Strategies for Node Embeddings with RDF2Vec in Knowledge Graphs
    Bram Steenwinckel, Gilles Vandewiele, Pieter Bonte, Michael Weyns, Heiko Paulheim, Petar Ristoski, Filip De Turck, Femke Ongenae · 2021 · Communications in computer and information science
22. Adversarial Graph Disentanglement With Component-Specific Aggregation
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23. Semi-supervised Tag Recommendation - Using Untagged Resources to Mitigate Cold-Start Problems
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24. Evaluating Statistical Tests for Within-Network Classifiers of Relational Data
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25. DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters
    W. O. K. Asiri Suranga Wijesinghe, Qing Wang · 2019 · arXiv (Cornell University)
26. Hypergraph Learning with Line Expansion.
    Chaoqi Yang, Ruijie Wang, Shuochao Yao, Tarek Abdelzaher · 2020 · arXiv (Cornell University)
27. Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More
    Aleksandar Bojchevski, Gasteiger, Johannes, Stephan Günnemann · 2020 · arXiv (Cornell University)
28. $p$-Laplacian Based Graph Neural Networks
    Guoji Fu, Peilin Zhao, Yatao Bian · 2021 · arXiv (Cornell University)
29. Imbalanced Node Classification With Synthetic Over-Sampling
    Tianxiang Zhao, X. D. Zhang, Suhang Wang · 2024 · IEEE Transactions on Knowledge and Data Engineering
30. A Survey of Large Language Models on Generative Graph Analytics: Query, Learning, and Applications
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31. GATSMOTE: Improving Imbalanced Node Classification on Graphs via Attention and Homophily
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32. DyGRAIN: An Incremental Learning Framework for Dynamic Graphs
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33. Graph Neural Network Meets Sparse Representation: Graph Sparse Neural Networks via Exclusive Group Lasso
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34. PSA-GNN: An augmented GNN framework with priori subgraph knowledge
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35. Toward Robust Graph Semi-Supervised Learning Against Extreme Data Scarcity
    Kaize Ding, Elnaz Nouri, Guoqing Zheng, Huan Liu, Ryen W. White · 2024 · IEEE Transactions on Neural Networks and Learning Systems
36. Mining node attributes for link prediction with a non-negative matrix factorization-based approach
    Zhili Zhao, Ahui Hu, Nana Zhang, Jiquan Xie, Zihao Du, Li Wan, Ruiyi Yan · 2024 · Knowledge-Based Systems
37. Deformable Graph Transformer
    Jinyoung Park, Seongjun Yun, Hyeonjin Park, Jaewoo Kang, Jisu Jeong, Kyung-Min Kim, Jung-Woo Ha, Hyunwoo J. Kim · 2025 · IEEE Transactions on Pattern Analysis and Machine Intelligence
38. Causal invariant geographic network representations with feature and structural distribution shifts
    Yuhan Wang, Silu He, Qinyao Luo, Hongyuan Yuan, Ling Zhao, Jiawei Zhu, Haifeng Li · 2025 · Future Generation Computer Systems
39. NMFE-SSCC: Non-negative matrix factorization ensemble for semi-supervised collective classification
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40. Iterative Hyperspectral Image Classification Using Spectral–Spatial Relational Features
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41. Document classification utilising ontologies and relations between documents
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42. Dimensionality Reduction on Heterogeneous Feature Space
    Xiaoxiao Shi, Philip S. Yu · 2012 · Proceedings
43. Reflect and correct
    Mustafa Bilgic, Lise C. Getoor · 2009 · ACM Transactions on Knowledge Discovery from Data
44. Distributed Representations of Subgraphs
    Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, B. Aditya Prakash · 2017 · IEEE ... International Conference on Data Mining workshops
45. Vertex nomination via seeded graph matching
    Heather G. Patsolic, Youngser Park, Vince Lyzinski, Carey E. Priebe · 2020 · Statistical Analysis and Data Mining The ASA Data Science Journal
46. Unifying Structural Proximity and Equivalence for Network Embedding
    Benyun Shi, Chunpeng Zhou, Hongjun Qiu, Xiaobin Xu, Jiming Liu · 2019 · IEEE Access
47. Multi-Task Learning Based Network Embedding
    Shanfeng Wang, Qixiang Wang, Maoguo Gong · 2020 · Frontiers in Neuroscience
48. KGAnet: a knowledge graph attention network for enhancing natural language inference
    Meina Song, Wen Ping Zhao, E Haihong · 2020 · Neural Computing and Applications
49. Longitudinal Citation Prediction using Temporal Graph Neural Networks
    Andreas Nugaard Holm, Barbara Plank, Dustin Wright, Isabelle Augenstein · 2020 · VBN Forskningsportal (Aalborg Universitet)
50. Automated Graph Learning via Population Based Self-Tuning GCN
    Ronghang Zhu, Zhiqiang Tao, Yaliang Li, Sheng Li · 2021 · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
51. Exploring an edge convolution and normalization based approach for link prediction in complex networks
    Zhiwei Zhang, Lin Cui, Jia Wu · 2021 · Journal of Network and Computer Applications
52. A novel attributed community detection by integration of feature weighting and node centrality
    Mehrdad Rostami, Mourad Oussalah · 2022 · Online Social Networks and Media
53. Stabilizing and Enhancing Link Prediction through Deepened Graph Auto-Encoders
    Xinxing Wu, Qiang Shawn Cheng · 2022 · International Joint Conference on Artificial Intelligence
54. Iterative Annotation of Multi-relational Social Networks
    Stéphane Peters, Ludovic Denoyer, Patrick Gallinari · 2010 · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
55. Collaborative boosting for activity classification in microblogs
    Yangqiu Song, Zhengdong Lu, Cane Wing-ki Leung, Qiang Yang · 2013 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
56. Predicting High Impact Academic Papers Using Citation Network Features
    Daniel McNamara, Paul Wong, Peter Christen, Kee Siong Ng · 2013 · Lecture notes in computer science
57. Node Embeddings and Exact Low-Rank Representations of Complex Networks
    Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis · 2020 · arXiv (Cornell University)
58. Learning with Hyperspherical Uniformity
    Weiyang Liu, Rongmei Lin, Liu, Zhen, Li Xiong, Bernhard Schölkopf, Adrian Weller · 2021 · arXiv (Cornell University)
59. Multimode Froth Flotation Process Operating Performance Assessment Based on Deep Embedded Graph Clustering Network
    Di Lu, Fuli Wang, Shu Wang, Kaiqing Bu, Kang Li, Xiang Ma · 2024 · IEEE Transactions on Industrial Informatics
60. GraphEdge: Dynamic graph partition and task scheduling for GNNs computing in edge network
    Wenjing Xiao, Chenglong Shi, Miaojiang Chen, Zhiquan Liu, Min Chen, Houbing Song · 2025 · Information Fusion
61. Oversmoothing alleviation in graph neural networks: a survey and unified view
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62. Multi-label collective classification via Markov chain based learning method
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63. From Entity Recognition to Entity Linking: A Survey of Advanced Entity Linking Techniques
    Hong-Jie Dai, Chi-Yang Wu, Richard Tzong-han, Wen−Lian Hsu · 2013
64. The generalization error of graph convolutional networks may enlarge with more layers
    Xianchen Zhou, Hongxia Wang · 2020 · Neurocomputing
65. A unified framework for convolution-based graph neural networks
    Xuran Pan, X. Y. Han, Chaofei Wang, Zhuo Li, Shiji Song, Gao Ming Huang, Cheng Wu · 2024 · Pattern Recognition
66. Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks
    Moshe Eliasof, Benjamin J. Bodner, Eran Treister · 2023 · IEEE Transactions on Neural Networks and Learning Systems
67. Link prediction based on higher-order structure extraction and autoencoder learning in directed networks
    Tao Yi, Shanfan Zhang, Zhan Bu, Jinwei Du, Changjian Fang · 2022 · Knowledge-Based Systems
68. Evolution-Driven Randomized Graph Convolutional Networks
    Zijia Zhang, Yaoming Cai, Wenyin Gong · 2022 · IEEE Transactions on Systems Man and Cybernetics Systems
69. Multi-Scale Distillation from Multiple Graph Neural Networks
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70. Self-Supervised Graphs for Audio Representation Learning With Limited Labeled Data
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71. A differentiable approach to the maximum independent set problem using dataless neural networks
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72. Defense against membership inference attack in graph neural networks through graph perturbation
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73. FocusedCleaner: Sanitizing Poisoned Graphs for Robust GNN-Based Node Classification
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74. A Comprehensive Review of the Oversmoothing in Graph Neural Networks
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75. Simple and Efficient Partial Graph Adversarial Attack: A New Perspective
    Guanghui Zhu, Mengyu Chen, Chunfeng Yuan, Yihua Huang · 2024 · IEEE Transactions on Knowledge and Data Engineering
76. A Dual Robust Graph Neural Network Against Graph Adversarial Attacks
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77. Complex Graph Analysis and Representation Learning: Problems, Techniques, and Applications
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78. GraphRARE: Reinforcement Learning Enhanced Graph Neural Network with Relative Entropy
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79. Lightweight image super-resolution network based on dynamic graph message passing and convolution mixer
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80. Discovering Factions in the Computational Linguistics Community
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81. Drug-target interaction prediction for drug repurposing with probabilistic similarity logic
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82. Learning and Detecting Patterns in Multi-Attributed Network Data.
    Georgiy Levchuk, Jennifer M. Roberts, Jared Freeman · 2012 · National Conference on Artificial Intelligence
83. INVESTIGATING MARKOV LOGIC NETWORKS FOR COLLECTIVE CLASSIFICATION
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84. It's Not About the Journey; It's About the Destination: Following Soft Paths Under Question-Guidance for Visual Reasoning
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85. DigGCN: Learning Compact Graph Convolutional Networks via Diffusion Aggregation
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86. Fitness landscape analysis of graph neural network architecture search spaces
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87. Learning Graph Representations With Maximal Cliques
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88. Probabilistic graphical models for semi-supervised traffic classification
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89. A Novel Framework for Node/Edge Attributed Graph Embedding
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90. Clustering Algorithm for Community Detection in Complex Network: A Comprehensive Review
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91. Label-Dependent Feature Extraction in Social Networks for Node Classification
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92. GraphTSNE: A Visualization Technique for Graph-Structured Data
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93. Structack: Structure-based Adversarial Attacks on Graph Neural Networks
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94. Graph sparsification with graph convolutional networks
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95. HP-GMN: Graph Memory Networks for Heterophilous Graphs
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96. A Generic Graph Sparsification Framework using Deep Reinforcement Learning
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97. Effective Backdoor Attack on Graph Neural Networks in Spectral Domain
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98. DWSSA: Alleviating over-smoothness for deep Graph Neural Networks
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99. Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-Based Similarity
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100. Few-shot Message-Enhanced Contrastive Learning for Graph Anomaly Detection
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