Un r\'esumeur \`a base de graphes, ind\'ep\'endant de la langue
Juan-Manuel Torres-Moreno, Javier Ramirez, Iria da Cunha

TL;DR
This paper introduces REG, a language-independent graph-based algorithm for automatic text summarization that models documents as graphs and computes sentence weights, successfully applied across three languages.
Contribution
The paper presents a novel language-independent graph-based method for automatic text summarization, capable of handling multiple languages.
Findings
Effective across three languages
Successfully computes sentence importance
Provides a language-independent summarization approach
Abstract
In this paper we present REG, a graph-based approach for study a fundamental problem of Natural Language Processing (NLP): the automatic text summarization. The algorithm maps a document as a graph, then it computes the weight of their sentences. We have applied this approach to summarize documents in three languages.
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Advanced Text Analysis Techniques
