Loading [MathJax]/jax/output/HTML-CSS/jax.js

Philippe Chassaing ; Lucas Gerin - Efficient estimation of the cardinality of large data sets

dmtcs:3492 - Discrete Mathematics & Theoretical Computer Science, January 1, 2006, DMTCS Proceedings vol. AG, Fourth Colloquium on Mathematics and Computer Science Algorithms, Trees, Combinatorics and Probabilities - https://doi.org/10.46298/dmtcs.3492
Efficient estimation of the cardinality of large data setsConference paper

Authors: Philippe Chassaing 1; Lucas Gerin 1

  • 1 Institut Élie Cartan de Nancy

Giroire has recently proposed an algorithm which returns the approximate number of distinct elements in a large sequence of words, under strong constraints coming from the analysis of large data bases. His estimation is based on statistical properties of uniform random variables in [0,1]. In this note we propose an optimal estimation, using Kullback information and estimation theory.


Volume: DMTCS Proceedings vol. AG, Fourth Colloquium on Mathematics and Computer Science Algorithms, Trees, Combinatorics and Probabilities
Section: Proceedings
Published on: January 1, 2006
Imported on: May 10, 2017
Keywords: cardinality,large multiset,approximate counting,[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS],[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM],[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]

9 Documents citing this article

Consultation statistics

This page has been seen 304 times.
This article's PDF has been downloaded 309 times.