Resumen

ITURBE-HERRERA, Alberto; ROJAS-VALDEZ, Armando; CASTRO-SANCHEZ, Noé Alejandro  y  SIERRA, Gerardo. Paraphrase detection based on Energy, Entropy and Textual Temperature. RISTI [online]. 2020, n.39, pp.35-51. ISSN 1646-9895.  https://doi.org/10.17013/risti.39.35-51.

Paraphrases are the reformulation of a text using different vocabulary to capture the original idea in our own words. In this research, a method for paraphrase detection is presented. We incorporate two variables, Entropy and Textual Temperature, into a previous model which implemented a Hopfield Network to generate a distance measure called Textual Energy. A Context of Free Affinity was generated using Entropy and Temperature based on the Ising Model, which allowed us to measure the semantic distribution between pairs of sentences. Our model was evaluated using Microsoft's Research Paraphrase Corpus improving the results of the previous model and was able to identify more than half of the paraphrases presented in the analyzed sample.

Palabras clave : Paraphrase detection; Textual Energy; Entropy; Textual Energy; Hopfield Network.

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