Nearest Embedded and Embedding Self-Nested Trees
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.
Cite
@article{arxiv.1709.02334,
title = {Nearest Embedded and Embedding Self-Nested Trees},
author = {Romain Azaïs},
journal= {arXiv preprint arXiv:1709.02334},
year = {2019}
}