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Spectral Clustering of Data Streams

The data is modeled as an m × n matrix P n points, each m-dimensional that is arriving as a stream, a point at a time. Our algorithm has two components stream framework StrFr and spectral clustering algorithm SpCl. SpCl works on an adjacency matrix representation of the points by recursively producing cuts on the graph thus defined. StrFr takes in the stream in chunks of size n1, converts a chunk into adjacency representation A, adjoins it with the compressed information of past chunks obtained through clustering, and uses SpCl to cluster it.