Embedding text-rich graph neural networks with sequence and topical semantic structures
暂无分享,去创建一个
Xiao Wang | Dongxiao He | Hanghang Tong | Di Jin | Jiawei Han | Zhizhi Yu | Ziyang Liu
[1] Xiao Wang,et al. AS-GCN: Adaptive Semantic Architecture of Graph Convolutional Networks for Text-Rich Networks , 2021, 2021 IEEE International Conference on Data Mining (ICDM).
[2] Di Jin,et al. Heterogeneous Graph Neural Network via Attribute Completion , 2021, WWW.
[3] Guojie Song,et al. Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels , 2021, WWW.
[4] Chenwei Zhang,et al. Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks , 2021, WWW.
[5] Philip S. Yu,et al. A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning , 2021, IEEE Transactions on Knowledge and Data Engineering.
[6] Ge Zhang,et al. Detecting Communities with Multiplex Semantics by Distinguishing Background, General, and Specialized Topics , 2020, IEEE Transactions on Knowledge and Data Engineering.
[7] Jiawei Han,et al. BiTe-GCN: A New GCN Architecture via Bidirectional Convolution of Topology and Features on Text-Rich Networks , 2020, WSDM.
[8] Wei Xiong,et al. BERT2DNN: BERT Distillation with Massive Unlabeled Data for Online E-Commerce Search , 2020, 2020 IEEE International Conference on Data Mining (ICDM).
[9] Hongbo Deng,et al. Gated Heterogeneous Graph Representation Learning for Shop Search in E-commerce , 2020, CIKM.
[10] Yuanchao Liu,et al. Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks , 2020, COLING.
[11] Ryan A. Rossi,et al. Graph Neural Networks with Heterophily , 2020, AAAI.
[12] Sundararajan Sellamanickam,et al. HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification , 2020, WSDM.
[13] Xiao Wang,et al. AM-GCN: Adaptive Multi-channel Graph Convolutional Networks , 2020, KDD.
[14] L. Akoglu,et al. Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs , 2020, NeurIPS.
[15] Karthik Subbian,et al. Learning Robust Models for e-Commerce Product Search , 2020, ACL.
[16] Yufeng Zhang,et al. Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks , 2020, ACL.
[17] Jingbo Shang,et al. NetTaxo: Automated Topic Taxonomy Construction from Text-Rich Network , 2020, WWW.
[18] Kevin Chen-Chuan Chang,et al. Geom-GCN: Geometric Graph Convolutional Networks , 2020, ICLR.
[19] Xien Liu,et al. Tensor Graph Convolutional Networks for Text Classification , 2020, AAAI.
[20] Philip S. Yu,et al. BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network , 2020, SDM.
[21] A. Micheli,et al. A Fair Comparison of Graph Neural Networks for Graph Classification , 2019, ICLR.
[22] Octavian-Eugen Ganea,et al. Constant Curvature Graph Convolutional Networks , 2019, ICML.
[23] Lidan Wang,et al. A Community-Enhanced Retrieval Model for Text-Rich Heterogeneous Information Networks , 2019, 2019 International Conference on Data Mining Workshops (ICDMW).
[24] Bingquan Liu,et al. A Neural Topic Model Based on Variational Auto-Encoder for Aspect Extraction from Opinion Texts , 2019, NLPCC.
[25] Yuchen Li,et al. Discovering Hypernymy in Text-Rich Heterogeneous Information Network by Exploiting Context Granularity , 2019, CIKM.
[26] Dacheng Tao,et al. SPAGAN: Shortest Path Graph Attention Network , 2019, IJCAI.
[27] Junzhou Huang,et al. DropEdge: Towards Deep Graph Convolutional Networks on Node Classification , 2019, ICLR.
[28] Jingrui He,et al. DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification , 2019, KDD.
[29] Jure Leskovec,et al. Position-aware Graph Neural Networks , 2019, ICML.
[30] Di Jin,et al. A Novel Generative Topic Embedding Model by Introducing Network Communities , 2019, WWW.
[31] Yanfang Ye,et al. Heterogeneous Graph Attention Network , 2019, WWW.
[32] Zhouchen Lin,et al. Multi-Stage Self-Supervised Learning for Graph Convolutional Networks , 2019, AAAI.
[33] Tieniu Tan,et al. Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification , 2019, IJCAI.
[34] Pietro Liò,et al. Deep Graph Infomax , 2018, ICLR.
[35] Yuan Luo,et al. Graph Convolutional Networks for Text Classification , 2018, AAAI.
[36] Ken-ichi Kawarabayashi,et al. Representation Learning on Graphs with Jumping Knowledge Networks , 2018, ICML.
[37] Pietro Liò,et al. Graph Attention Networks , 2017, ICLR.
[38] Zhiyuan Liu,et al. End-to-End Neural Ad-hoc Ranking with Kernel Pooling , 2017, SIGIR.
[39] Jure Leskovec,et al. Inductive Representation Learning on Large Graphs , 2017, NIPS.
[40] Phil Blunsom,et al. Discovering Discrete Latent Topics with Neural Variational Inference , 2017, ICML.
[41] Yan Zhang,et al. Mining E-commercial data: A text-rich heterogeneous network embedding approach , 2017, 2017 International Joint Conference on Neural Networks (IJCNN).
[42] Nick Craswell,et al. Learning to Match using Local and Distributed Representations of Text for Web Search , 2016, WWW.
[43] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[44] Xueqi Cheng,et al. Text Matching as Image Recognition , 2016, AAAI.
[45] Xueqi Cheng,et al. A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations , 2015, AAAI.
[46] Deli Zhao,et al. Network Representation Learning with Rich Text Information , 2015, IJCAI.
[47] Hang Li,et al. Convolutional Neural Network Architectures for Matching Natural Language Sentences , 2014, NIPS.
[48] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[49] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[50] Jie Tang,et al. ArnetMiner: extraction and mining of academic social networks , 2008, KDD.
[51] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[52] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[53] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .