Affinity Propagation Clustering for Large Scale Dataset
Gu Ruijun, Jiacai Wang, Geng Chen, Shenglei Chen · Jisuanji gongcheng · 2010
Affinity Propagation(AP)clustering takes the full similarity matrix to perform propagation,which limits its application in large scale dataset.An improved affinity propagation clustering is proposed specially for processing large dataset,which fully utilizes local distribution to add constraint like semi-supervised clustering to construct sparse similarity matrix.AP runs on sparse similarity matrix to obtain an initial cluster partition,and runs iteratively on the exemplars until it obtains a reasonable partition.Experimental results demonstrate that improved affinity propagation performs better both in processing scale and processing time.