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Network Embedding

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

Papers

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Showing 376–400 of 403 papers

TitleStatusHype
Community Aware Random Walk for Network Embedding—0
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vecCode0
metapath2vec: Scalable Representation Learning for Heterogeneous NetworksCode0
Full-Network Embedding in a Multimodal Embedding Pipeline—0
Equivalence between LINE and Matrix Factorization—0
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via RankingCode0
Demographic Inference on Twitter using Recursive Neural Networks—0
CANE: Context-Aware Network Embedding for Relation ModelingCode0
Attributed Network Embedding for Learning in a Dynamic Environment—0
An Out-of-the-box Full-network Embedding for Convolutional Neural Networks—0
struc2vec: Learning Node Representations from Structural IdentityCode0
Bib2vec: Embedding-based Search System for Bibliographic Information—0
Distributed Representations of Signed Networks—0
Font Size: Community Preserving Network EmbeddingCode0
Name Disambiguation in Anonymized Graphs using Network EmbeddingCode0
Heterogeneous Information Network Embedding for Meta Path based Proximity—0
Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author IdentificationCode0
Pairwise FastText Classifier for Entity Disambiguation—0
Identity-sensitive Word Embedding through Heterogeneous Networks—0
A General Framework for Content-enhanced Network Representation Learning—0
Deep Coevolutionary Network: Embedding User and Item Features for Recommendation—0
Predict Anchor Links across Social Networks via an Embedding Approach—0
Aligning Users Across Social Networks Using Network Embedding—0
Structural Deep Network EmbeddingCode0
Video Tracking Using Learned Hierarchical Features—0
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