document: Duplicate detection in click streams We consider the problem of finding duplicates in data streams . Duplicate detection in data streams is utilized in various applications including fraud detection . We develop a solution based on Bloom Filters ( 9 ) , and discuss the space and time requirements for running the proposed algorithm in both the contexts of sliding , and landmark stream windows . We run a comprehensive set of experiments , using both real and synthetic click streams , to evaluate the performance of the proposed solution . The results demonstrate that the proposed solution yields extremely low error rates .
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