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Network embedding methods aim at learning low-dimensional latent representation of nodes in a network.
Singular value decomposition and least squares solutions
Gene H Golub and Christian Reinsch · 1970
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An information flow model for conflict and fission in small groups
Wayne W Zachary · 1977
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Multidimensional scaling
Joseph B Kruskal and Myron Wish · 1978
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Principal component analysis
Svante Wold, Kim Esbensen, and Paul Geladi · 1987
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Spectral graph theory
Fan RK Chung · 1997
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Nonlinear dimensionality reduction by locally linear embedding
Sam T Roweis and Lawrence K Saul · 2000
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A global geometric framework for nonlinear dimensionality reduction
Joshua B Tenenbaum, Vin De Silva, and John C Langford · 2000
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Laplacian eigenmaps and spectral techniques for embedding and clustering
Mikhail Belkin and Partha Niyogi · 2002
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A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin · 2003
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Efficient, high-quality force-directed graph drawing
Yifan Hu · 2005
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Relational learning via latent social dimensions
Lei Tang and Huan Liu · 2009
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Leveraging social media networks for classification
Lei Tang and Huan Liu · 2011
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
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Neural word embedding as implicit matrix factorization
Omer Levy and Yoav Goldberg · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
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Deepwalk: Online learning of social representations
Bryan Perozzi, Rami Al-Rfou, and Steven Skiena · 2014
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Grarep: Learning graph representations with global structural information
Shaosheng Cao, Wei Lu, and Qiongkai Xu · 2015
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Heterogeneous network embedding via deep architectures
Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C Aggarwal, and Thomas S Huang · 2015
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Exploiting latent social listening representations for music recommendations
Chih-Ming Chen, Po-Chuan Chien, Yu-Ching Lin, Ming-Feng Tsai, and Yi-Hsuan Yang · 2015
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Learning image and user features for recommendation in social networks
Xue Geng, Hanwang Zhang, Jingwen Bian, and Tat-Seng Chua · 2015
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Jiwei Li, Alan Ritter, and Dan Jurafsky · 2015
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Exact age prediction in social networks
Bryan Perozzi and Steven Skiena · 2015
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Line: Large-scale information network embedding
Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, and Qiaozhu Mei · 2015
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Deep graph kernels
Pinar Yanardag and SVN Vishwanathan · 2015
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Network representation learning with rich text information
Cheng Yang, Zhiyuan Liu, Deli Zhao, Maosong Sun, and Edward Y Chang · 2015
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Multi-modal bayesian embeddings for learning social knowledge graphs
Zhilin Yang, Jie Tang, and William Cohen · 2015
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Learning features from large-scale, noisy and social image-tag collection
Hanwang Zhang, Xindi Shang, Huanbo Luan, Yang Yang, and Tat-Seng Chua · 2015
Learning of multimodal representations with random walks on the click graph
Fei Wu, Xinyan Lu, Jun Song, Shuicheng Yan, Zhongfei Mark Zhang, Yong Rui, and Yueting Zhuang · 2016
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A neural network approach to joint modeling social networks and mobile trajectories
Cheng Yang, Maosong Sun, Wayne Xin Zhao, Zhiyuan Liu, and Edward Y Chang · 2016
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Revisiting semi-supervised learning with graph embeddings
Zhilin Yang, William Cohen, and Ruslan Salakhutdinov · 2016
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Homophily, structure, and content augmented network representation learning
Daokun Zhang, Jie Yin, Xingquan Zhu, and Chengqi Zhang · 2016
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Learning from collective intelligence: Feature learning using social images and tags
Hanwang Zhang, Xindi Shang, Huanbo Luan, Meng Wang, and Tat-Seng Chua · 2016
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Representation learning for measuring entity relatedness with rich information
Yu Zhao, Zhiyuan Liu, and Maosong Sun · 2015
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Deep neural networks for learning graph representations
Shaosheng Cao, Wei Lu, and Qiongkai Xu · 2016
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Query-based music recommendations via preference embedding
Chih-Ming Chen, Ming-Feng Tsai, Yu-Ching Lin, and Yi-Hsuan Yang · 2016
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Incorporate group information to enhance network embedding
Jifan Chen, Qi Zhang, and Xuanjing Huang · 2016
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Extracting semantics from random walks on wikipedia: Comparing learning and counting methods
Alexander Dallmann, Thomas Niebler, Florian Lemmerich, and Andreas Hotho · 2016
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Community-based question answering via heterogeneous social network learning
Hanyin Fang, Fei Wu, Zhou Zhao, Xinyu Duan, Yueting Zhuang, and Martin Ester · 2016
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Expert finding for community-based question answering via ranking metric network learning
Zhou Zhao, Qifan Yang, Deng Cai, Xiaofei He, and Yueting Zhuang · 2016
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Learning edge representations via low-rank asymmetric projections
Sami Abu-El-Haija, Bryan Perozzi, and Rami Al-Rfou · 2017
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Watch your step: Learning graph embeddings through attention
Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou, and Alex Alemi · 2017
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Deepbrowse: Similarity-based browsing through large lists
Haochen Chen, Arvind Ram Anantharam, and Steven Skiena · 2017
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Fast, warped graph embedding: Unifying framework and one-click algorithm
Siheng Chen, Sufeng Niu, Leman Akoglu, Jelena Kovačević, and Christos Faloutsos · 2017
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Vector-based similarity measurements for historical figures
Yanqing Chen, Bryan Perozzi, and Steven Skiena · 2017
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metapath2vec: Scalable representation learning for heterogeneous networks
Yuxiao Dong, Nitesh V Chawla, and Ananthram Swami · 2017
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Don’t walk, skip! online learning of multi-scale network embeddings
Bryan Perozzi, Vivek Kulkarni, Haochen Chen, and Steven Skiena · 2017
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Network embedding as matrix factorization: Unifying deepwalk, line, pte, and node2vec
Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, and Jie Tang · 2017
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Cane: Context-aware network embedding for relation modeling
Cunchao Tu, Han Liu, Zhiyuan Liu, and Maosong Sun · 2017
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Transnet: Translation-based network representation learning for social relation extraction
Cunchao Tu, Zhengyan Zhang, Zhiyuan Liu, and Maosong Sun · 2017
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Signed network embedding in social media
Suhang Wang, Jiliang Tang, Charu Aggarwal, Yi Chang, and Huan Liu · 2017
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Community preserving network embedding
Xiao Wang, Peng Cui, Jing Wang, Jian Pei, Wenwu Zhu, and Shiqiang Yang · 2017
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Embedding of embedding (eoe): Joint embedding for coupled heterogeneous networks
Linchuan Xu, Xiaokai Wei, Jiannong Cao, and Philip S Yu · 2017
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Shuhan Yuan, Xintao Wu, and Yang Xiang · 2017
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Scalable graph embedding for asymmetric proximity
Chang Zhou, Yuqiong Liu, Xiaofei Liu, Zhongyi Liu, and Jun Gao · 2017
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Harp: Hierarchical representation learning for networks
Haochen Chen, Bryan Perozzi, Yifan Hu, and Steven Skiena · 2018
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