A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications
暂无分享,去创建一个
[1] Xuelong Li,et al. Unsupervised Large Graph Embedding , 2017, AAAI.
[2] Ichiro Sakata,et al. Representation learning for geospatial areas using large-scale mobility data from smart card , 2016, UbiComp Adjunct.
[3] Subu Surendran. Graph Embedding and Dimensionality Reduction - A Survey , 2013 .
[4] Gene H. Golub,et al. Singular value decomposition and least squares solutions , 1970, Milestones in Matrix Computation.
[5] Zhiyuan Liu,et al. Representation Learning of Knowledge Graphs with Entity Descriptions , 2016, AAAI.
[6] Shaowen Wang,et al. Regions, Periods, Activities: Uncovering Urban Dynamics via Cross-Modal Representation Learning , 2017, WWW.
[7] Jia Wang,et al. Topological Recurrent Neural Network for Diffusion Prediction , 2017, 2017 IEEE International Conference on Data Mining (ICDM).
[8] Li Guo,et al. Context-Dependent Knowledge Graph Embedding , 2015, EMNLP.
[9] Omer Levy,et al. Improving Distributional Similarity with Lessons Learned from Word Embeddings , 2015, TACL.
[10] Li Guo,et al. SSE: Semantically Smooth Embedding for Knowledge Graphs , 2017, IEEE Transactions on Knowledge and Data Engineering.
[11] Hwann-Tzong Chen,et al. Semantic manifold learning for image retrieval , 2005, MULTIMEDIA '05.
[12] Richard S. Zemel,et al. Gated Graph Sequence Neural Networks , 2015, ICLR.
[13] Feiping Nie,et al. Nonlinear Dimensionality Reduction with Local Spline Embedding , 2009, IEEE Transactions on Knowledge and Data Engineering.
[14] Edwin R. Hancock,et al. Spherical and Hyperbolic Embeddings of Data , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[15] Arif Mahmood,et al. Using Geodesic Space Density Gradients for Network Community Detection , 2017, IEEE Transactions on Knowledge and Data Engineering.
[16] Nicholas Jing Yuan,et al. Collaborative Knowledge Base Embedding for Recommender Systems , 2016, KDD.
[17] T. D. Morley,et al. Eigenvalues of the Laplacian of a graph , 1985 .
[18] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[19] Chengqi Zhang,et al. User Profile Preserving Social Network Embedding , 2017, IJCAI.
[20] Tat-Seng Chua,et al. Learning Image and User Features for Recommendation in Social Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[21] Joan Bruna,et al. Spectral Networks and Locally Connected Networks on Graphs , 2013, ICLR.
[22] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[23] Abdolreza Mirzaei,et al. Hierarchical graph embedding in vector space by graph pyramid , 2017, Pattern Recognit..
[24] Ah Chung Tsoi,et al. The Graph Neural Network Model , 2009, IEEE Transactions on Neural Networks.
[25] Hady Wirawan Lauw,et al. Probabilistic Latent Document Network Embedding , 2014, 2014 IEEE International Conference on Data Mining.
[26] Jieping Ye,et al. Hypergraph spectral learning for multi-label classification , 2008, KDD.
[27] Zhiyuan Liu,et al. Fast Network Embedding Enhancement via High Order Proximity Approximation , 2017, IJCAI.
[28] Mukund Balasubramanian,et al. The Isomap Algorithm and Topological Stability , 2002, Science.
[29] H. Howie Huang,et al. G-Store: High-Performance Graph Store for Trillion-Edge Processing , 2016, SC16: International Conference for High Performance Computing, Networking, Storage and Analysis.
[30] Alán Aspuru-Guzik,et al. Convolutional Networks on Graphs for Learning Molecular Fingerprints , 2015, NIPS.
[31] Jure Leskovec,et al. node2vec: Scalable Feature Learning for Networks , 2016, KDD.
[32] Carlos Guestrin,et al. Distributed GraphLab : A Framework for Machine Learning and Data Mining in the Cloud , 2012 .
[33] Hans-Peter Kriegel,et al. A Three-Way Model for Collective Learning on Multi-Relational Data , 2011, ICML.
[34] Kilian Q. Weinberger,et al. Learning a kernel matrix for nonlinear dimensionality reduction , 2004, ICML.
[35] Jonathan Masci,et al. Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[36] Zhendong Mao,et al. Knowledge Graph Embedding: A Survey of Approaches and Applications , 2017, IEEE Transactions on Knowledge and Data Engineering.
[37] Jason Weston,et al. Translating Embeddings for Modeling Multi-relational Data , 2013, NIPS.
[38] Qiongkai Xu,et al. GraRep: Learning Graph Representations with Global Structural Information , 2015, CIKM.
[39] Heng Ji,et al. Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding , 2016, KDD.
[40] Zhiyuan Liu,et al. Learning Entity and Relation Embeddings for Knowledge Graph Completion , 2015, AAAI.
[41] Wenwu Zhu,et al. Structural Deep Network Embedding , 2016, KDD.
[42] Chengqi Zhang,et al. Homophily, Structure, and Content Augmented Network Representation Learning , 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).
[43] Qiaozhu Mei,et al. PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks , 2015, KDD.
[44] Palash Goyal,et al. Graph Embedding Techniques, Applications, and Performance: A Survey , 2017, Knowl. Based Syst..
[45] Charu C. Aggarwal,et al. Heterogeneous Network Embedding via Deep Architectures , 2015, KDD.
[46] Jason Weston,et al. Learning Structured Embeddings of Knowledge Bases , 2011, AAAI.
[47] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[48] Yueting Zhuang,et al. Expert Finding for Community-Based Question Answering via Ranking Metric Network Learning , 2016, IJCAI.
[49] Zhiyuan Liu,et al. Knowledge Representation Learning with Entities, Attributes and Relations , 2016, IJCAI.
[50] Alexander J. Smola,et al. Distributed large-scale natural graph factorization , 2013, WWW.
[51] Xavier Bresson,et al. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering , 2016, NIPS.
[52] Hanqing Lu,et al. Community-Based Question Answering via Contextual Ranking Metric Network Learning , 2017, AAAI.
[53] Daniel R. Figueiredo,et al. struc2vec: Learning Node Representations from Structural Identity , 2017, KDD.
[54] Tim Weninger,et al. ProjE: Embedding Projection for Knowledge Graph Completion , 2016, AAAI.
[55] Tat-Seng Chua,et al. Learning from Collective Intelligence , 2016, ACM Trans. Multim. Comput. Commun. Appl..
[56] Zhiyuan Liu,et al. Representation Learning of Knowledge Graphs with Hierarchical Types , 2016, IJCAI.
[57] Minlie Huang,et al. GAKE: Graph Aware Knowledge Embedding , 2016, COLING.
[58] Ben Y. Zhao,et al. On the Embeddability of Random Walk Distances , 2013, Proc. VLDB Endow..
[59] Nitesh V. Chawla,et al. metapath2vec: Scalable Representation Learning for Heterogeneous Networks , 2017, KDD.
[60] Mathias Niepert,et al. Learning Convolutional Neural Networks for Graphs , 2016, ICML.
[61] James Demmel,et al. Fast linear algebra is stable , 2006, Numerische Mathematik.
[62] Yi Yang,et al. Structured Embedding via Pairwise Relations and Long-Range Interactions in Knowledge Base , 2015, AAAI.
[63] Xiaolong Jin,et al. Predict Anchor Links across Social Networks via an Embedding Approach , 2016, IJCAI.
[64] Wenhua Wang,et al. Local and Global Regressive Mapping for Manifold Learning with Out-of-Sample Extrapolation , 2010, AAAI.
[65] Cheng Li,et al. DeepCas: An End-to-end Predictor of Information Cascades , 2016, WWW.
[66] Carlo Zaniolo,et al. Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment , 2016, IJCAI.
[67] Gerhard Weikum,et al. WWW 2007 / Track: Semantic Web Session: Ontologies ABSTRACT YAGO: A Core of Semantic Knowledge , 2022 .
[68] Alharbi Basma,et al. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties , 2016 .
[69] David Haussler,et al. Convolution kernels on discrete structures , 1999 .
[70] Jason Weston,et al. Question Answering with Subgraph Embeddings , 2014, EMNLP.
[71] Qing Zhang,et al. Not All Links Are Created Equal: An Adaptive Embedding Approach for Social Personalized Ranking , 2016, SIGIR.
[72] Pradeep Dubey,et al. Navigating the maze of graph analytics frameworks using massive graph datasets , 2014, SIGMOD Conference.
[73] Le Song,et al. Discriminative Embeddings of Latent Variable Models for Structured Data , 2016, ICML.
[74] Jure Leskovec,et al. Inductive Representation Learning on Large Graphs , 2017, NIPS.
[75] Yufei Han,et al. Partially Supervised Graph Embedding for Positive Unlabelled Feature Selection , 2016, IJCAI.
[76] Yueting Zhuang,et al. Community-Based Question Answering via Heterogeneous Social Network Learning , 2016, AAAI.
[77] Han Xiao,et al. From One Point to a Manifold: Knowledge Graph Embedding for Precise Link Prediction , 2015, IJCAI.
[78] Kevin Chen-Chuan Chang,et al. Distance-Aware DAG Embedding for Proximity Search on Heterogeneous Graphs , 2018, AAAI.
[79] Steven Skiena,et al. DeepWalk: online learning of social representations , 2014, KDD.
[80] Chang Zhou,et al. Scalable Graph Embedding for Asymmetric Proximity , 2017, AAAI.
[81] Philip S. Yu,et al. Cross View Link Prediction by Learning Noise-resilient Representation Consensus , 2017, WWW.
[82] Pinar Yanardag,et al. Deep Graph Kernels , 2015, KDD.
[83] Bo Zhang,et al. Discriminative Deep Random Walk for Network Classification , 2016, ACL.
[84] Mingzhe Wang,et al. LINE: Large-scale Information Network Embedding , 2015, WWW.
[85] Jason Weston,et al. A semantic matching energy function for learning with multi-relational data , 2013, Machine Learning.
[86] Yueting Zhuang,et al. Community-Based Question Answering via Asymmetric Multi-Faceted Ranking Network Learning , 2017, AAAI.
[87] Tony Jebara,et al. Minimum Volume Embedding , 2007, AISTATS.
[88] Pascal Vincent,et al. Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[89] Kevin Chen-Chuan Chang,et al. Subgraph-augmented Path Embedding for Semantic User Search on Heterogeneous Social Network , 2018, WWW.
[90] Praveen Paritosh,et al. Freebase: a collaboratively created graph database for structuring human knowledge , 2008, SIGMOD Conference.
[91] Feiping Nie,et al. Flexible Orthogonal Neighborhood Preserving Embedding , 2017, IJCAI.
[92] Guillaume Bouchard,et al. Complex Embeddings for Simple Link Prediction , 2016, ICML.
[93] Jian Pei,et al. Asymmetric Transitivity Preserving Graph Embedding , 2016, KDD.
[94] James P. Callan,et al. Explicit Semantic Ranking for Academic Search via Knowledge Graph Embedding , 2017, WWW.
[95] Minlie Huang,et al. SSP: Semantic Space Projection for Knowledge Graph Embedding with Text Descriptions , 2016, AAAI.
[96] Ivor W. Tsang,et al. A Unified Feature Selection Framework for Graph Embedding on High Dimensional Data , 2015, IEEE Transactions on Knowledge and Data Engineering.
[97] Pierre Vandergheynst,et al. Geometric Deep Learning: Going beyond Euclidean data , 2016, IEEE Signal Process. Mag..
[98] Xiaofei He,et al. Locality Preserving Projections , 2003, NIPS.
[99] Yoshua Bengio,et al. On the Properties of Neural Machine Translation: Encoder–Decoder Approaches , 2014, SSST@EMNLP.
[100] Tony Jebara,et al. Structure preserving embedding , 2009, ICML '09.
[101] Zhiyuan Liu,et al. Max-Margin DeepWalk: Discriminative Learning of Network Representation , 2016, IJCAI.
[102] Kevin Chen-Chuan Chang,et al. From Node Embedding To Community Embedding , 2016, ArXiv.
[103] Yuanzhuo Wang,et al. Locally Adaptive Translation for Knowledge Graph Embedding , 2015, AAAI.
[104] Jun Zhao,et al. Knowledge Graph Embedding via Dynamic Mapping Matrix , 2015, ACL.
[105] Jian Pei,et al. Community Preserving Network Embedding , 2017, AAAI.
[106] Meng Wang,et al. Learning content–social influential features for influence analysis , 2016, International Journal of Multimedia Information Retrieval.
[107] Kevin Chen-Chuan Chang,et al. Learning Community Embedding with Community Detection and Node Embedding on Graphs , 2017, CIKM.
[108] Li Guo,et al. Semantically Smooth Knowledge Graph Embedding , 2015, ACL.
[109] Jiawei Han,et al. Large-Scale Embedding Learning in Heterogeneous Event Data , 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).
[110] Chengqi Zhang,et al. Tri-Party Deep Network Representation , 2016, IJCAI.
[111] Jie Tang,et al. Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs , 2015, IJCAI.
[112] Stephen Lin,et al. Graph Embedding and Extensions: A General Framework for Dimensionality Reduction , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[113] Dacheng Tao,et al. Signed Laplacian Embedding for Supervised Dimension Reduction , 2014, AAAI.
[114] Rui Zhang,et al. Incorporating Knowledge Graph Embeddings into Topic Modeling , 2017, AAAI.
[115] Yueting Zhuang,et al. Learning of Multimodal Representations With Random Walks on the Click Graph , 2016, IEEE Transactions on Image Processing.
[116] Adriano Veloso,et al. Unsupervised and Scalable Algorithm for Learning Node Representations , 2017, ICLR.
[117] Devdatt P. Dubhashi,et al. Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings , 2015, KDD.
[118] Hans-Peter Kriegel,et al. Shortest-path kernels on graphs , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).
[119] Li Wen,et al. Dimensionality reduction on Anchorgraph with an efficient Locality Preserving Projection , 2016, Neurocomputing.
[120] Wei Lu,et al. Deep Neural Networks for Learning Graph Representations , 2016, AAAI.
[121] Ichiro Sakata,et al. Geospatial Area Embedding Based on the Movement Purpose Hypothesis Using Large-Scale Mobility Data from Smart Card , 2016 .
[122] Mohamed Nadif,et al. A Semi-NMF-PCA Unified Framework for Data Clustering , 2017, IEEE Transactions on Knowledge and Data Engineering.
[123] Jianxin Li,et al. On the Representation and Embedding of Knowledge Bases beyond Binary Relations , 2016, IJCAI.
[124] Lorenzo Rosasco,et al. Holographic Embeddings of Knowledge Graphs , 2015, AAAI.
[125] Shuicheng Yan,et al. Graph Embedding and Extensions: A General Framework for Dimensionality Reduction , 2007 .
[126] Jun Zhao,et al. Knowledge Graph Completion with Adaptive Sparse Transfer Matrix , 2016, AAAI.
[127] Yizhou Yu,et al. Piecewise Flat Embedding for Image Segmentation , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[128] Kurt Mehlhorn,et al. Weisfeiler-Lehman Graph Kernels , 2011, J. Mach. Learn. Res..
[129] John A Bullinaria,et al. Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD , 2012, Behavior research methods.
[130] Enhong Chen,et al. Learning Deep Representations for Graph Clustering , 2014, AAAI.
[131] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[132] Anton van den Hengel,et al. Semidefinite Programming , 2014, Computer Vision, A Reference Guide.
[133] Joan Bruna,et al. Deep Convolutional Networks on Graph-Structured Data , 2015, ArXiv.
[134] Pascal Frossard,et al. Graph-based Isometry Invariant Representation Learning , 2017, ICML.
[135] Junbin Gao,et al. Laplacian Regularized Low-Rank Representation and Its Applications , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[136] Michalis Vazirgiannis,et al. Matching Node Embeddings for Graph Similarity , 2017, AAAI.
[137] Joachim M. Buhmann,et al. Multidimensional Scaling and Data Clustering , 1994, NIPS.
[138] S. V. N. Vishwanathan,et al. Graph kernels , 2007 .
[139] Juan-Zi Li,et al. Text-Enhanced Representation Learning for Knowledge Graph , 2016, IJCAI.
[140] Deli Zhao,et al. Network Representation Learning with Rich Text Information , 2015, IJCAI.
[141] Li Liu,et al. Aligning Users across Social Networks Using Network Embedding , 2016, IJCAI.
[142] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[143] Feiping Nie,et al. Capped Lp-Norm Graph Embedding for Photo Clustering , 2016, ACM Multimedia.
[144] Ruslan Salakhutdinov,et al. Revisiting Semi-Supervised Learning with Graph Embeddings , 2016, ICML.
[145] Kevin Chen-Chuan Chang,et al. Semantic Proximity Search on Heterogeneous Graph by Proximity Embedding , 2017, AAAI.
[146] Zhiyuan Liu,et al. Representation Learning for Measuring Entity Relatedness with Rich Information , 2015, IJCAI.
[147] Jens Lehmann,et al. DBpedia - A crystallization point for the Web of Data , 2009, J. Web Semant..
[148] Jiawei Han,et al. Spectral regression: a unified subspace learning framework for content-based image retrieval , 2007, ACM Multimedia.
[149] Zhen Wang,et al. Knowledge Graph Embedding by Translating on Hyperplanes , 2014, AAAI.
[150] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[151] Danqi Chen,et al. Reasoning With Neural Tensor Networks for Knowledge Base Completion , 2013, NIPS.
[152] Daniel Dajun Zeng,et al. Predicting user's multi-interests with network embedding in health-related topics , 2016, 2016 International Joint Conference on Neural Networks (IJCNN).
[153] Kurt Mehlhorn,et al. Efficient graphlet kernels for large graph comparison , 2009, AISTATS.
[154] Han Xiao,et al. TransG : A Generative Model for Knowledge Graph Embedding , 2015, ACL.
[155] Reynold Xin,et al. GraphX: Graph Processing in a Distributed Dataflow Framework , 2014, OSDI.