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Updated: Jul 30, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

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Published on: August 30, 2013

On the fractal patterns of language structures.

Leonardo Costa Ribeiro¹, Américo Tristão Bernardes², Heliana Mello³

¹Departamento de Ciências Econômicas, Faculdade de Ciências Econômicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brasil.

|May 18, 2023

Summary

This study uses Natural Language Processing (NLP) and fractal dimensions to analyze linguistic patterns across 17 languages. Language structures tend to cluster based on their evolutionary relationships found in phylogenetic trees.

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Area of Science:

Computational Linguistics
Artificial Intelligence
Phylogenetics

Background:

Natural Language Processing (NLP) extracts information from unstructured text using AI.
NLP applications include sentiment analysis, summarization, and translation.
Understanding structural linguistic patterns across languages is an ongoing challenge.

Purpose of the Study:

To identify similar structural linguistic patterns among diverse languages using NLP.
To represent languages in a multi-dimensional space based on linguistic features.
To explore the relationship between linguistic similarity and language evolutionary history.

Main Methods:

Applied the word2vec algorithm to create 100-dimensional vector representations for words in 17 languages.
Calculated multi-fractal dimensions for each language's structural representation.
Utilized fractal dimensions and token-dictionary size rate to position languages in a 3D space.

Main Results:

Generated multi-dimensional vector representations for English, Portuguese, German, Spanish, Russian, French, Chinese, Japanese, Korean, Italian, Arabic, Hebrew, Basque, Dutch, Swedish, Finnish, and Estonian.
Identified multi-fractal dimensions characterizing the linguistic structures.
Visualized language relationships in a 3D space based on linguistic and fractal features.

Conclusions:

Language proximity in the 3D space correlates with their evolutionary distance on the Phylogenetic tree.
Linguistic structures exhibit patterns that reflect historical language development.
This approach offers a novel method for quantitatively comparing and classifying languages.