Jianxin Li

Breaking Structural Isolation: Scalable Graph Clustering via Community-Aware Sampling and Structural Entropy

This work proposes SCISE, a unsupervised graph clustering framework that significantly outperforms state-of-the-art algorithms, and designs a Structural Contrastive Learning module that refines edge weights based on intra-batch structural similarity, guiding the encoder to learn representations in higher-order structural space.