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参考文献リスト メインページ

4.1節 はじめに

タイトル 著者名 リンク 登場順
DeepWalk: Online Learning of Social Representations Perozzi et al 2014 arxiv 1
LINE: Large-scale Information Network Embedding Tang et al 2015 arxiv 2
node2vec: Scalable Feature Learning for Networks Grover and Leskovec 2016 arxiv 3
struc2vec: Learning Node Representations from Structural Identity Ribeiro et al 2017 arxiv 4
Preserving Local and Global Information for Network Embedding Ma et al 2017 arxiv 5
PRUNE: Preserving Proximity and Global Ranking for Network Embedding Lai et al 2017 リンク 6
RaRE: Social Rank Regulated Large-scale Network Embedding Gu et al 2018 リンク 7
Community Preserving Network Embedding Wang et al 2017c リンク 8

4.2節 単純グラフのグラフ埋め込み

タイトル 著者名 リンク 登場順
DeepWalk: Online Learning of Social Representations Perozzi et al 2014 arxiv 1
node2vec: Scalable Feature Learning for Networks Grover and Leskovec 2016 arxiv 2
LINE: Large-scale Information Network Embedding Tang et al 2015 arxiv 3
Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation Fouss et al 2007 リンク 4
Local Graph Partitioning using PageRank Vectors Andersen et al 2006 PDF 5
Distributed Representations of Words and Phrases and their Compositionality Mikolov et al 2013 arxiv 6
GraRep: Learning Graph Representations with Global Structural Information Cao et al 2015 リンク 7
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics Gutmann and Hyvärinen 2012 リンク 8
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec Qiu et al 2018b arxiv 9
struc2vec: Learning Node Representations from Structural Identity Ribeiro et al 2017 arxiv 10
Structural equivalence: Meaning and definition, computation and application Sailer 1978 リンク 11
FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space Salvador and Chan 2007 PDF 12
Preserving Local and Global Information for Network Embedding Ma et al 2017 arxiv 13
Modularity and community structure in networks Newman 2006 arxiv 14
Community Preserving Network Embedding Wang et al 2017c リンク 15
Community Detection in Attributed Graphs: An Embedding Approach Li et al 2018d リンク 16

4.3節 複雑グラフ上のグラフ埋め込み

タイトル 著者名 リンク 登場順
Heterogeneous Network Embedding via Deep Architectures Chang et al 2015 リンク 1
metapath2vec: Scalable Representation Learning for Heterogeneous Networks Dong et al 2017 リンク 2
BiNE: Bipartite Network Embedding Gao et al 2018b PDF 3
Multi-Dimensional Network Embedding with Hierarchical Structure Ma et al 2018d リンク 4
Signed Network Embedding in Social Media Wang et al 2017b リンク 5
Sitting closer to friends than enemies, revisited Cygan et al 2012 arxiv 6
Is Distrust the Negation of Trust? The Value of Distrust in Social Media Tang et al 2014b リンク 7
Structural Deep Embedding for Hyper-Networks Tu et al 2018 arxiv 8
Continuous-Time Dynamic Network Embeddings Nguyen et al 2018 リンク 9

4.5節 参考文献

タイトル 著者名 リンク 登場順
HONE: Higher-Order Network Embeddings Rossi et al 2018 arxiv 1
Asymmetric Transitivity Preserving Graph Embedding Ou et al 2016 PDF 2
Learning social network embeddings for predicting information diffusion Bourigault et al 2014 リンク 3
Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification Chen and Sun 2017 arxiv 4
Heterogeneous Information Network Embedding for Recommendation Shi et al 2018a arxiv 5
ActiveHNE: Active Heterogeneous Network Embedding Chen et al 2019b arxiv 6
Bipartite Network Embedding via Effective Integration of Explicit and Implicit Relations Wang et al 2019j リンク 7
Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs He et al 2019 arxiv 8
mvn2vec: Preservation and Collaboration in Multi-View Network Embedding Shi et al 2018b arxiv 9
SNE: Signed Network Embedding Yuan et al 2017 arxiv 10
Attributed Signed Network Embedding Wang et al 2017a リンク 11
Heterogeneous Hyper-Network Embedding Baytas et al 2018 リンク 12
Attributed Network Embedding for Learning in a Dynamic Environment Li et al 2017a arxiv 13
Dynamic Network Embedding by Modeling Triadic Closure Process Zhou et al 2018b リンク 14
Representation Learning on Graphs: Methods and Applications Hamilton et al 2017b arxiv 15
Graph Embedding Techniques, Applications, and Performance: A Survey Goyal and Ferrara 2018 arxiv 16
A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications Cai et al 2018 arxiv 17
A Survey on Network Embedding Cui et al 2018 arxiv 18
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