Words of fixed size q are commonly referred to as $q$-grams. We consider the problem of $q$-gram filtration, a method commonly used to speed upsequence comparison. We are interested in the statistics of the number of $q$-grams common to two random texts (where multiplicities are not counted) in the non uniform Bernoulli model. In the exact and dependent model, when omitting border effects, a $q$-gramin a random sequence depends on the $q-1$ preceding $q$-grams. In an approximate and independent model, we draw randomly a $q$-gram at each position, independently of the others positions. Using ball and urn models, we analyze the independent model. Numerical simulations show that this model is an excellent first order approximationto the dependent model. We provide an algorithm to compute the moments.

Source : oai:HAL:hal-01183917v1

Volume: DMTCS Proceedings vol. AC, Discrete Random Walks (DRW'03)

Section: Proceedings

Published on: January 1, 2003

Submitted on: May 10, 2017

Keywords: Sequence comparison,Bernoulli model,urn models,[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],[INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG]

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