Semantic Exploration of Textual Analogies for Advanced Plagiarism Detection

EasyChair Preprint no. 12504

Abstract

This study explores textual analogies in French within the context of plagiarism detection, adopting a semantic approach. By combining traditional methods with advanced models such as BERT and GPT, the paper proposes a hybrid model to 8 enhance detection efficiency. Comparative evaluation highlights the model's ability to detect subtle similarities and paraphrases. The approach represents a significant advancement in accurate plagiarism detection by leveraging deep contextual understanding and the reformulation capabilities of integrated models.

Keyphrases: BERT, combined model, GPT, Natural Language Processing, Plagiarism, semantics, Textual Analogies

@Booklet{EasyChair:12504,
  author = {Elyah Frisco Andriantsialo and Volatiana Marielle Ratianantitra and Thomas Mahatody},
  title = {Semantic Exploration of Textual Analogies for Advanced Plagiarism Detection},
  howpublished = {EasyChair Preprint no. 12504},

  year = {EasyChair, 2024}}