Scalable information organization

We present three scalable extensions of the star algorithm for information organization that use sampling. The star algorithm organizes a document collection into clusters that are naturally induced by the topic structure of collection, via a computationally efficient cover by dense subgraphs. We also provide supporting data from extensive experiments.

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