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孟加拉语新闻文章数据集

Asif Mohammed Saad1, Umme Niraj Mahi1, Md Shahidul Salim1

  • 1Khulna University of Engineering & Technology, Khulna 9203, Bangladesh.

Data in brief
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此摘要是机器生成的。

这项研究引入了一个全面的孟加拉新闻数据集,包含超过190万篇文章. 该资源支持孟加拉自然语言处理和特定领域的大型语言模型的进步.

关键词:
分类 分类 分类 分类.数据分析数据分析自然语言处理自然语言处理.

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科学领域:

  • 自然语言处理 (NLP) 是一种自然语言处理.
  • 数据科学数据科学数据科学
  • 计算语言学 计算语言学

背景情况:

  • 一个新的,广泛的孟加拉语新闻数据集已经从九个主要新闻来源中编制出来.
  • 该数据集包括体育,经济,政治和技术等多个类别的超过190万篇文章.
  • 它包括各种属性,如每个文章的标题,内容,发布时间,标签和元信息.

研究的目的:

  • 为NLP研究提供一个更新的,大规模的孟加拉语新闻数据集.
  • 为孟加拉国促进开发特定领域的人工智能模型.
  • 为了使数据科学家能够研究孟加拉语语言理论.

主要方法:

  • 从九个知名新闻网站收集了超过190万篇孟加拉新闻文章.
  • 在各种领域分类文章,包括体育,经济,政治,技术,健康和艺术.
  • 用标题,内容,时间,标签,元和类别等属性对数据集进行结构化.

主要成果:

  • 一个庞大的孟加拉语新闻数据集,包含超过190万篇文章.
  • 该数据集包括对NLP任务至关重要的各种属性.
  • 数据涵盖了广泛的新闻类别.

结论:

  • 提出的孟加拉语数据集是NLP社区的宝贵资源.
  • 它将加速孟加拉语NLP的研究和为孟加拉国量身定制的AI模型的创建.
  • 数据集支持机器学习和深度学习模型的开发,用于文章分类.