An event-adaptive incremental framework for transient community detection in temporal networks
A novel evolutionary incremental approach called Event Adaptive Incremental Learning Non-Negative Matrix Factorization (EA-iNMF) is proposed, which integrates event-adaptive learning with an incremental update mechanism to efficiently identify optimal time spans corresponding to peak user engagement.