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原文連結
論文資訊
- 類型:已發表論文
- 日期:2017-04-24
摘要
複雜系統s are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer 網絡 where each layer represents one type of interaction. These layers may be interdependent in complicated ways, revealing different kinds of structure in the 網絡. In this work we present a generative model, and an efficient expectation-maximization algorithm, which allows us to perform inference tasks such as community detection and link prediction in this setting. Our model assumes overlapping communities that are common between the layers, while allowing these communities to affect each layer in a different way, including arbitrary mixtures of assortative, disassortative, or directed structure. It also gives us a 數學ly principled way to define the interdependenc
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