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Network Embedding

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Network Embedding, also known as "Network Representation Learning", is a collective term for techniques for mapping graph nodes to vectors of real numbers in a multidimensional space. To be useful, a good embedding should preserve the structure of the graph. The vectors can then be used as input to various network and graph analysis tasks, such as link prediction

Source: Tutorial on NLP-Inspired Network Embedding

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/ghentdatascience/csne-public

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CSNE: Conditional Signed Network Embedding

https://github.com/Ange1o/GPSP

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GPSP: Graph Partition and Space Projection based Approach for Heterogeneous Network Embedding

https://github.com/B-Deprez/GARG-AML

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GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering

https://github.com/Dtrycode/ToupleGDD

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ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning

https://github.com/EmbNet01/EmbNetworks

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Efficient Network Embedding by Approximate Equitable Partitions

https://github.com/GTmac/FastRP

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Fast and Accurate Network Embeddings via Very Sparse Random Projection

https://github.com/GeminiLight/flag-vne

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FlagVNE: A Flexible and Generalizable Reinforcement Learning Framework for Network Resource Allocation

https://github.com/GemsLab/PhUSION

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Node Proximity Is All You Need: Unified Structural and Positional Node and Graph Embedding

https://github.com/GentleZhu/HEER

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Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks

https://github.com/HKUST-KnowComp/vertex-reinforced-random-walk

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Vertex-reinforced Random Walk for Network Embedding

https://github.com/JieyuZ2/NEP

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Neural Embedding Propagation on Heterogeneous Networks

https://github.com/KnowledgeDiscovery/StrGNN

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Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs

https://github.com/LPioL/MultiVERSE

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MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approach

https://github.com/Leo-Q-316/ImGAGN

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ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph Networks

https://github.com/Linda-sunshine/JNET

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JNET: Learning User Representations via Joint Network Embedding and Topic Embedding

https://github.com/RingBDStack/dynamic_network_embedding

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Dynamic Network Embedding via Incremental Skip-gram with Negative Sampling

https://github.com/RinneSz/Social-Collaborative-Metric-Learning

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Where are we in embedding spaces? A Comprehensive Analysis on Network Embedding Approaches for Recommender Systems

https://github.com/ShansYu/mrate

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Multi-Relation Aware Temporal Interaction Network Embedding

https://github.com/SkBlaz/DNR

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Deep Node Ranking for Neuro-symbolic Structural Node Embedding and Classification

https://github.com/SotirisKot/Content-Aware-N2V

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Embedding Biomedical Ontologies by Jointly Encoding Network Structure and Textual Node Descriptors

https://github.com/Vachik-Dave/Neural-Brane-Neural-Bayesian-Personalized-Ranking-for-Attributed-Network-Embedding

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Neural-Brane: Neural Bayesian Personalized Ranking for Attributed Network Embedding

https://github.com/Wenlin-Wang/VHE19

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Improving Textual Network Learning with Variational Homophilic Embeddings

https://github.com/XinyiZ001/mSHINE

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mSHINE: A Multiple-meta-paths Simultaneous Learning Framework for Heterogeneous Information Network Embedding

https://github.com/ZINUX1998/DyCSC

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DyCSC: Modeling the Evolutionary Process of Dynamic Networks Based on Cluster Structure

https://github.com/ZW-ZHANG/RandNE

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Billion-scale Network Embedding with Iterative Random Projection

https://github.com/aida-ugent/CSNE

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CSNE: Conditional Signed Network Embedding

https://github.com/aida-ugent/DeBayes

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DeBayes: a Bayesian Method for Debiasing Network Embeddings

https://github.com/aida-ugent/NRL4LP

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Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress?

https://github.com/albertlordsun/bhgnn-rt

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BHGNN-RT: Network embedding for directed heterogeneous graphs

https://github.com/alibaba/euler

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IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation

https://github.com/benedekrozemberczki/MUSAE

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Multi-scale Attributed Node Embedding

https://github.com/benedekrozemberczki/diff2vec

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Fast Sequence-Based Embedding with Diffusion Graphs

https://github.com/brochier/expert_finding

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New Datasets and a Benchmark of Document Network Embedding Methods for Scientific Expert Finding

https://github.com/brochier/gvnr

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Global Vectors for Node Representations

https://github.com/brochier/idne

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Inductive Document Network Embedding with Topic-Word Attention

https://github.com/cenyk1230/GATNE

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Representation Learning for Attributed Multiplex Heterogeneous Network

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