Automatic semantic processing, focusing on textual coherence, to support the production of written news
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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.
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Hernández Osuna, S., & Ferreira Cabrera, A. (2018). Automatic semantic processing, focusing on textual coherence, to support the production of written news. Estudios Filológicos, (58), 97–122. https://doi.org/10.4067/S0071-17132016000200005
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