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Oct, 2017
大规模属性图的归纳表征学习
Representation Learning in Large Attributed Graphs
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Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou, John Boaz Lee, Xiangnan Kong...
TL;DR
本研究提出了一个基于属性随机游走的框架用于推断网络表示学习,该框架可以更广泛地应用于现有的机器学习方法中,并解决了现有方法中节点身份相关性的固有问题。
Abstract
graphs
(networks) are ubiquitous and allow us to model entities (nodes) and the dependencies (edges) between them. Learning a useful feature representation from graph data lies at the heart and success of many
machine l
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