2018 NetworkEmbeddingAsMatrixFactori

• (Qiu et al., 2018) ⇒ Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, and Jie Tang. (2018). “Network Embedding As Matrix Factorization: Unifying DeepWalk, LINE, PTE, and Node2vec.” In: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining. ISBN:978-1-4503-5581-0 doi:10.1145/3159652.3159706

Subject Headings: node2vec.

Cited By

• http://scholar.google.com/scholar?q=%222018%22+Network+Embedding+As+Matrix+Factorization%3A+Unifying+DeepWalk%2C+LINE%2C+PTE%2C+and+Node2vec
• http://dl.acm.org/citation.cfm?id=3159652.3159706&preflayout=flat#citedby

Quotes

Abstract

Since the invention of word2vec, the skip-gram model has significantly advanced the research of network embedding, such as the recent emergence of the DeepWalk, LINE, PTE, and node2vec approaches. In this work, we show that all of the aforementioned models with negative sampling can be unified into the matrix factorization framework with closed forms. Our analysis and proofs reveal that: (1) DeepWalk empirically produces a low-rank transformation of a network's normalized Laplacian matrix; (2) LINE, in theory, is a special case of DeepWalk when the size of vertices' context is set to one; (3) As an extension of LINE, PTE can be viewed as the joint factorization of multiple networks» Laplacians; (4) node2vec is factorizing a matrix related to the stationary distribution and transition probability tensor of a 2nd-order random walk. We further provide the theoretical connections between skip-gram based network embedding algorithms and the theory of graph Laplacian. Finally, we present the NetMF method as well as its approximation algorithm for computing network embedding. Our method offers significant improvements over DeepWalk and LINE for conventional network mining tasks. This work lays the theoretical foundation for skip-gram based network embedding methods, leading to a better understanding of latent network representation learning.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2018 NetworkEmbeddingAsMatrixFactori	Jie Tang Kuansan Wang Yuxiao Dong Jiezhong Qiu Hao Ma Jian Li			Network Embedding As Matrix Factorization: Unifying DeepWalk, LINE, PTE, and Node2vec				10.1145/3159652.3159706		2018