Multi-view Subspace Clustering for High-dimensional Data
نویسندگان
چکیده
The data today is towards more observations and very high dimensions. Large high-dimensional data are usually sparse and contain many classes/clusters. For example, large text data in the vector space model often contains many classes of documents represented in thousands of terms. It has become a rule rather than the exception that clusters in high-dimensional data occur in subspaces of data, so subspace clustering methods are required in high-dimensional data clustering.
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