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Abstract : |
popescul,ungar We introduce a simple and efficient method for clustering and identifying temporal trends in hyper-linked document databases. Our method can scale to large datasets because it exploits the underlying regularity often found in hyper-linked document databases. Because of this scalability, we can use our method to study the temporal trends of individual clusters in a statistically meaningful manner. As an example of our approach, we give a summary of the temporal trends found in a scientific literature database with thousands of documents. 1, |
