推荐系统初学者系列（8）-- Graph Embedding（网络嵌入表示）做Top-K推荐_network embedding as matrix factorization: unifyin

七月在线视频推荐：
七月在线

上一篇：推荐系统初学者系列（7）-- Surprise库做Top-K推荐
下一篇：推荐系统初学者系列（9）-- 非负矩阵分解NMF

awesome-network-embedding

Also called network representation learning, graph embedding, knowledge embedding, etc.

The task is to learn the representations of the vertices from a given network.

Graph Embedding相关文献

Paper References with the implementation(s)

• AspEm
  • AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks
  • [paper]
  • [Python]
• gat2vec
  • gat2vec: Representation learning for attributed graphs
  • [paper]
  • [Python]
• FSCNMF
  • FSCNMF: Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks
  • [paper]
  • [Python]
• SIDE
  • SIDE: Representation Learning in Signed Directed Networks
  • [paper]
  • [Python]
  • [Site]
• AWE
  • Anonymous Walk Embeddings, ICML’18
  • [paper]
  • [Python]
• BiNE
  • BiNE: Bipartite Network Embedding, SIGIR’18
  • [paper]
  • [Python]
• HOPE
  • Asymmetric Transitivity Preserving Graph Embedding
  • [KDD 2016]
  • [Python]
• VERSE
  • VERSE, Versatile Graph Embeddings from Similarity Measures
  • [Arxiv] [[WWW 2018]]
  • [Python]
• AGNN
  • Attention-based Graph Neural Network for semi-supervised learning
  • [ICLR 2018 OpenReview (rejected)]
  • [Python]
• Hyperbolics
  • Representation Tradeoffs for Hyperbolic Embeddings
  • [Arxiv]
  • [Python]
• DGCNN
  • An End-to-End Deep Learning Architecture for Graph Classification
  • [AAAI 2018]
  • [Lua] [Python]
• structure2vec
  • Discriminative Embeddings of Latent Variable Models for Structured Data
  • [Arxiv]
  • [Python]
• Decagon
  • Decagon, Graph Neural Network for Multirelational Link Prediction
  • [Arxiv] [SNAP] [[ISMB 2018]]
  • [Python]
• Ohmnet
  • Feature Learning in Multi-Layer Networks
  • [Arxiv] [SNAP]
  • [Python]
• SDNE
  • Structural Deep Network Embedding
  • [KDD 2016]
  • [Python]
• STWalk
  • STWalk: Learning Trajectory Representations in Temporal Graphs]
  • [Arxiv]
  • [Python]
• LoNGAE
  • Learning to Make Predictions on Graphs with Autoencoders
  • [Arxiv]
  • [Python]
• RSDNE
  • RSDNE: Exploring Relaxed Similarity and Dissimilarity from Completely-imbalanced Labels for Network Embedding., AAAI 2018
  • [Matlab]
• FastGCN
  • FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
  • [Arxiv], [ICLR 2018 OpenReview]
  • [Python]
• GEMSEC
  • GEMSEC: Graph Embedding with Self Clustering, arXiv 2018
  • [Python]
• diff2vec
  • Fast Sequence Based Embedding with Diffusion Graphs, CompleNet 2018
  • [Python]
• Poincare
  • Poincaré Embeddings for Learning Hierarchical Representations, NIPS 2017
  • [PyTorch] [Python] [C++]
• PEUNE
  • PRUNE: Preserving Proximity and Global Ranking for Network Embedding, NIPS 2017
  • [code]
• ASNE
  • Attributed Social Network Embedding, arxiv’17
  • [arxiv] [Python]
• GraphWave
  • Spectral Graph Wavelets for Structural Role Similarity in Networks,
  • [arxiv], [ICLR 2018 OpenReview]
  • [Python]
• StarSpace
  • StarSpace: Embed All The Things!, arxiv’17
  • [code]
• proNet-core
  • Vertex-Context Sampling for Weighted Network Embedding, arxiv’17
  • [arxiv] [code]
• struc2vec
  • struc2vec: Learning Node Representations from Structural Identity, KDD’17
  • [Python]
• ComE
  • Learning Community Embedding with Community Detection and Node Embedding on Graphs, CIKM’17
  • [Python]
• M-NMF
  • Community Preserving Network Embedding, AAAI’17
  • [Python]
• GraphSAGE
  • Inductive Representation Learning on Large Graphs, NIPS’17
  • [arxiv] [TF] [PyTorch]
• ICE
  • ICE: Item Concept Embedding via Textual Information, SIGIR’17
  • [demo] [code]
• metapath2vec
  • metapath2vec: Scalable Representation Learning for Heterogeneous Networks, KDD’17
  • [paper] [project website]
• GCN
  • Semi-Supervised Classification with Graph Convolutional Networks, ICLR’17
  • [arxiv] [Python Tensorflow]
• GAE
  • Variational Graph Auto-Encoders, arxiv
  • [arxiv] [Python Tensorflow]
• CANE
  • CANE: Context-Aware Network Embedding for Relation Modeling, ACL’17
  • [paper] [Python]
• TransNet
  • TransNet: Translation-Based Network Representation Learning for Social Relation Extraction, IJCAI’17
  • [Python Tensorflow]
• cnn_graph
  • Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering, NIPS’16
  • [Python]
• ConvE
  • Convolutional 2D Knowledge Graph Embeddings, arxiv
  • [source]
• node2vec
  • node2vec: Scalable Feature Learning for Networks, KDD’16
  • [arxiv] [Python] [Python-2] [Python-3] [C++]
• DNGR
  • Deep Neural Networks for Learning Graph Representations, AAAI’16
  • [Matlab] [Python Keras]
• HolE
  • Holographic Embeddings of Knowledge Graphs, AAAI’16
  • [Python-sklearn] [Python-sklearn2]
• ComplEx
  • Complex Embeddings for Simple Link Prediction, ICML’16
  • [arxiv] [Python]
• MMDW
  • Max-Margin DeepWalk: Discriminative Learning of Network Representation, IJCAI’16
  • [paper] [Java]
• planetoid
  • Revisiting Semi-supervised Learning with Graph Embeddings, ICML’16
  • [arxiv] [Python]
• PowerWalk
  • PowerWalk: Scalable Personalized PageRank via Random Walks with Vertex-Centric Decomposition, CIKM’16
  • [code]
• LINE
  • LINE: Large-scale information network embedding, WWW’15
  • [arxiv] [C++] [Python TF] [Python Theano/Keras]
• PTE
  • PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks, KDD’15
  • [C++]
• GraRep
  • Grarep: Learning graph representations with global structural information, CIKM’15
  • [Matlab]
• KB2E
  • Learning Entity and Relation Embeddings for Knowledge Graph Completion, AAAI’15
  • [paper] [C++] [faster version]
• TADW
  • Network Representation Learning with Rich Text Information, IJCAI’15
  • [paper] [Matlab]
• DeepWalk
  • DeepWalk: Online Learning of Social Representations, KDD’14
  • [arxiv] [Python] [C++]
• GEM
  • Graph Embedding Techniques, Applications, and Performance: A Survey
  • [arxiv] [Python]

Paper References

MetaGraph2Vec, MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding

PinSAGE, Graph Convolutional Neural Networks for Web-Scale Recommender Systems

Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning, WSDM '18

Adversarial Network Embedding, arxiv

Role2Vec, Learning Role-based Graph Embeddings

edge2vec, Feature Propagation on Graph: A New Perspective to Graph Representation
Learning

MINES, Multi-Dimensional Network Embedding with Hierarchical Structure

Walk-Steered Convolution for Graph Classification

Deep Feature Learning for Graphs, arxiv’17

Watch Your Step: Learning Graph Embeddings Through Attention, arxiv’17

Fast Linear Model for Knowledge Graph Embeddings, arxiv’17

Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec, arxiv’17

A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications, arxiv’17

Representation Learning on Graphs: Methods and Applications, IEEE DEB’17

CONE, CONE: Community Oriented Network Embedding, arxiv’17

LANE,
Label Informed Attributed Network Embedding, WSDM’17

Graph2Gauss,
Deep Gaussian Embedding of Attributed Graphs: Unsupervised Inductive Learning via Ranking, arxiv
[Bonus Animation]

Scalable Graph Embedding for Asymmetric Proximity, AAAI’17

Query-based Music Recommendations via Preference Embedding, RecSys’16

Tri-party deep network representation, IJCAI’16

Heterogeneous Network Embedding via Deep Architectures, KDD’15

Neural Word Embedding As Implicit Matrix Factorization, NIPS’14

Distributed large-scale natural graph factorization, WWW’13

From Node Embedding To Community Embedding, arxiv

Walklets: Multiscale Graph Embeddings for Interpretable Network Classification, arxiv

Comprehend DeepWalk as Matrix Factorization, arxiv

Conference & Workshop

13th International Workshop on Mining and Learning with Graphs, MLG’17

WWW-18 Tutorial Representation Learning on Networks, WWW’18

Related List

awesome-embedding-models

Must-read papers on network representation learning (NRL) / network embedding (NE)

Must-read papers on knowledge representation learning (KRL) / knowledge embedding (KE)

Network Embedding Resources

awesome-embedding-models

2vec-type embedding models

Related Project

Stanford Network Analysis Project website