High-order network reconstruction based on community division and key nodes

Key Points

• The proposed framework significantly reduces computational complexity by combining local and global reconstruction methods.
• Efficient reconstruction is achieved through a two-phase algorithm that integrates community division and key node identification.
• Initial reconstruction utilizes compressed sensing theory to analyze interaction networks and identify community structures effectively.
• Experimental results show notable improvements in both running time and reconstruction performance on various networks.

Abstract