Finding Top-k Most Frequent Items in Distributed Streams in the Time-Sliding Window Model
Résumé
We propose a new probabilistic algorithm to find the top-k most recent and frequent items in distributed streams. This algorithm significantly improves upon the reliability and accuracy of existing results, while significantly reducing the memory footprint needed by each of the distributed nodes to solve this problem.
| Origine | Fichiers produits par l'(les) auteur(s) |
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