Automatic semantic processing, focusing on textual coherence, to support the production of written news

Article Sidebar

pdf (Español (España))
Published: Feb 15, 2018
DOI: https://doi.org/10.4067/S0071-17132016000200005
Keywords:
- Natural Language Processing
- coherence
- Latent Semantic Analysis
- politic news

Main Article Content

Sergio Hernández Osuna
Universidad de Concepción, Departamento de Comunicación Social, Concepción, Chile.
Anita Ferreira Cabrera
Universidad de Concepción, Departamento de Español, Concepción, Chile.

Abstract

The following article presents the steps to build a semantic analysis module focused on the prediction of textual coherence, programmed in Python 3. The steps described include the work done in the design of a tool for automatic recopilation of the corpus (politic news), another destined to prepare the texts collected for further processing, up to the final design tool that performs the analysis of the texts. The method used for this is the Latent Semantic Analysis. Finally, the article presents the results of tests performed in order to test the tool, through texts processing, with the goal of watching sensitivity in the evaluation of textual coherence.

Article Details

How to Cite
Hernández Osuna, S., & Ferreira Cabrera, A. (2018). Automatic semantic processing, focusing on textual coherence, to support the production of written news. Philological Studies, (58), 97–122. https://doi.org/10.4067/S0071-17132016000200005
Issue
No. 58 (2016)
Section
Artículos
Author Biography

Sergio Hernández Osuna, Universidad de Concepción, Departamento de Comunicación Social, Concepción, Chile.

El estudio en procesamiento de lenguaje natural que se presenta en este artículo se ha desarrollado en el contexto del proyecto de investigación FONDECYT 1140651 en lo que compete a los avances del Sistema Tutorial Inteligente para mejorar la precisión lingüística (Investigadora Responsable: Dra. Anita Ferreira Cabrera).