Modularity-like objective function in annotated networks

doi:10.1007/s11467-017-0657-y

2017-01-27

Jiarong Xie

Bing-Hong Wang *

DOI：10.1007/s11467-017-0657-y

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摘要

En 中文

We ascertain the modularity-like objective function whose optimization is equivalent to the maximum likelihood in annotated networks. We demonstrate that the modularity-like objective function is a linear combination of modularity and conditional entropy. In contrast with statistical inference methods, in our method, the influence of the metadata is adjustable; when its influence is strong enough, the metadata can be recovered. Conversely, when it is weak, the detection may correspond to another partition. Between the two, there is a transition. This paper provides a concept for expanding the scope of modularity methods.

Keyword:

community structure

annotated networks

modularity

objective function

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期刊

Frontiers of Physics

IF:

5.3

论文数:

1.4K

被引数:

3.7K

机构

chinese academy of sciences

学者数:

56.7W

论文数: 45.0W

被引数: 704

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