A Clustering Method with Graph Maximum Decoding Information

arXiv:2403.13846v1 Announce Type: new
Abstract: The clustering method based on graph models has garnered increased attention for its widespread applicability across various knowledge domains. Its adaptability to integrate seamlessly with other relevant applications endows the graph model-based clustering analysis with the ability to robustly extract "natural associations" or "graph structures" within datasets, facilitating the modelling of relationships between data points. Despite its efficacy, the current clustering method utilizing the graph-based model overlooks the uncertainty associated with random walk access between …

abstract adaptability analysis applications arxiv attention clustering cs.ai cs.lg datasets decoding domains extract graph information knowledge natural the graph type