Nearest embedded and embedding self-nested trees

Romain Azaïs 1, 2
1 BIGS - Biology, genetics and statistics
Inria Nancy - Grand Est, IECL - Institut Élie Cartan de Lorraine
Abstract : Self-nested trees present a systematic form of redundancy in their subtrees and thus achieve optimal compression rates by DAG compression. A method for quantifying the degree of self-similarity of plants through self-nested trees has been introduced by Godin and Ferraro in 2010. The procedure consists in computing a self-nested approximation, called the nearest embedding self-nested tree, that both embeds the plant and is the closest to it. In this paper, we propose a new algorithm that computes the nearest embedding self-nested tree with a smaller overall complexity, but also the nearest embedded self-nested tree. We show from simulations that the latter is mostly the closest to the initial data, which suggests that this better approximation should be used as a privileged measure of the degree of self-similarity of plants.
Type de document :
Pré-publication, Document de travail
2017
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https://hal.archives-ouvertes.fr/hal-01584078
Contributeur : Romain Azaïs <>
Soumis le : vendredi 8 septembre 2017 - 11:56:08
Dernière modification le : jeudi 27 septembre 2018 - 15:15:55

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  • HAL Id : hal-01584078, version 1
  • ARXIV : 1709.02334

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Romain Azaïs. Nearest embedded and embedding self-nested trees. 2017. 〈hal-01584078〉

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