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An adaptive high-order knowledge guided multi-objective evolutionary algorithm for dynamic community detection
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AI
DOI：10.1016/j.asoc.2026.114935.png)
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Abstract
En 中文
• We propose an adaptive high-order knowledge-guided MOEA to effectively solve the dynamic community detection problem. • We design a new encoding strategy and a novel biased mutation operator to better harness high-order knowledge. • A high-order NMI-based objective function is developed with adaptive weights based on temporal snapshot influence. • Our method achieved superior results and automatically determined the number of communities without requiring any prior knowledge.
Keywords:
dynamic community detection
multi-objective evolutionary algorithm
high-order knowledge
adaptive weighting
community detection
Journal
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6.6
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1.4W
Citations:
4.8W
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