A Semi-supervised Clustering via Orthogonal Projection

作者:Cui Peng*; Zhang Ru bo
来源:2nd ISECS International Colloquium on Computing, Communication, Control and Management (CCCM 2009), China,Hainan,Sanya, 2009-08-08 to 2009-08-09.
DOI:10.1109/cccm.2009.5267927

摘要

As dimensionality is very high, image feature space is usually complex. For effectively processing this space, technology of dimensionality reduction is widely used. Semi-supervised clustering incorporates limited information into unsupervised clustering in order to improve clustering performance. However, many existing semi-supervised clustering methods can not be used to handle high-dimensional sparse data. To solve this problem, we proposed a semi-supervised fuzzy clustering method via constrained orthogonal projection. With results of experiments on different datasets, it shows the method has good clustering performance for handling high dimensionality data.

全文