2014 DeepWalkOnlineLearningofSocialR

• (Perozzi et al., 2014) ⇒ Bryan Perozzi, Rami Al-Rfou, and Steven Skiena. (2014). “DeepWalk: Online Learning of Social Representations.” In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) Journal. ISBN:978-1-4503-2956-9 doi:10.1145/2623330.2623732

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222014%22+DeepWalk%3A+Online+Learning+of+Social+Representations
• http://dl.acm.org/citation.cfm?id=2623330.2623732&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; deep learning; latent representations; learning with partial labels; network classification; online learning; social networks; statistical

Abstract

We present DeepWalk, a novel approach for learning latent representations of vertices in a network. These latent representations encode social relations in a continuous vector space, which is easily exploited by statistical models. DeepWalk generalizes recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences of words to graphs.

DeepWalk uses local information obtained from truncated random walks to learn latent representations by treating walks as the equivalent of sentences. We demonstrate DeepWalk's latent representations on several multi-label network classification tasks for social networks such as BlogCatalog, Flickr, and YouTube. Our results show that DeepWalk outperforms challenging baselines which are allowed a global view of the network, especially in the presence of missing information. DeepWalk's representations can provide F1 scores up to 10% higher than competing methods when labeled data is sparse. In some experiments, DeepWalk's representations are able to outperform all baseline methods while using 60% less training data.

DeepWalk is also scalable. It is an online learning algorithm which builds useful incremental results, and is trivially parallelizable. These qualities make it suitable for a broad class of real world applications such as network classification, and anomaly detection.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 DeepWalkOnlineLearningofSocialR	Steven Skiena Bryan Perozzi Rami Al-Rfou			DeepWalk: Online Learning of Social Representations				10.1145/2623330.2623732		2014