Indonesian News Text Summarization Using MBART Algorithm

Scientific Journal of Informatics Pub Date : 2024-02-29 DOI:10.15294/sji.v11i1.49224

Rahma Hayuning Astuti, Muljono Muljono, Sutriawan Sutriawan

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引用次数: 0

Abstract

Purpose: Technology advancements have led to the production of a large amount of textual data. There are numerous locations where one can find textual information sources, including blogs, news portals, and websites. Kompas, BBC, Liputan 6, CNN, and other news portals are a few websites that offer news in Indonesian. The purpose of this study was to explore the effectiveness of using mBART in text summarization for Bahasa Indonesia.Methods: This study uses mBART, a transformer architecture, to perform fine-tuning to generate news article summaries in Bahasa Indonesia. Evaluation was conducted using the ROUGE method to assess the quality of the summaries produced.Results: Evaluation using the ROUGE metric showed better results, with ROUGE-1 of 35.94, ROUGE-2 of 16.43, and ROUGE-L of 29.91. However, the performance of the model is still not optimal compared to existing models in text summarization for another language.Novelty: The novelty of this research lies in the use of mBART for text summarization, specifically adapted for Bahasa Indonesia. In addition, the findings also contribute to understanding the challenges and opportunities of improving text summarization techniques in the Indonesian context.

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使用 MBART 算法总结印尼新闻文本

目的：技术进步产生了大量文本数据。人们可以在许多地方找到文本信息源，包括博客、新闻门户网站和网站。Kompas、BBC、Liputan 6、CNN 和其他新闻门户网站是提供印尼语新闻的几个网站。本研究的目的是探讨在印尼语文本摘要中使用 mBART 的有效性：本研究使用 mBART（一种转换器架构）进行微调，以生成印尼语的新闻文章摘要。使用 ROUGE 方法进行评估，以评估所生成摘要的质量：使用 ROUGE 指标进行的评估结果较好，ROUGE-1 为 35.94，ROUGE-2 为 16.43，ROUGE-L 为 29.91。新颖性：这项研究的新颖性在于使用 mBART 进行文本摘要，并特别针对印尼语进行了调整。此外，研究结果还有助于理解在印尼语环境中改进文本摘要技术所面临的挑战和机遇。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Scientific Journal of Informatics

自引率

0.00%

发文量

审稿时长

24 weeks