关键词: 半监督聚类, 谱聚类

Abstract: Semi-supervised clustering employs a small amount of labeled data to aid unsupervised learning. In this paper a new semi-supervised clustering method based on spectral clustering was proposed. Making use of the information the labeled data contains, the distance matrix derived from data was modified and then the spectral clustering method was uesed to get the final clusters according to the modified distance matrix. Experimental result demonstrates that compared with previously proposed semi-supervised clustering algorithm this method produces better clusters.

Key words: semi-supervised clustering, spectral clustering