: Visual Abstraction of Dynamic Network via Improved Multi-class Blue Noise Sampling (IMAGE)

Higher Education Press

: Visual Abstraction of Dynamic Network via Improved Multi-class Blue Noise Sampling

Caption

High school student face-to-face contact dataset. After the MCBN (b), the local block effect of some edges (see (a) ③ and ④) nearly disappear in (b) ③ and ④. After the EOD-ES (c), many invisible contact pairs in (a) with frequent communication stand out. However, numerous outliers in (a) ① and ② are lost in (c) ① and ②. (a) No Sampling; (b) The MCBN; (c) The EOD-ES; (d) After the E-MCBN sampling algorithm; (e) The distributions of the edge counts of the high school dataset before and after E-MCBN

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HIGHER EDUCATION PRESS LIMITED COMPANY

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