索米科伦:数据集从孟加拉语数学文本中发现方程
Tanjim Taharat Aurpa1, Kazi Noshin Fariha2, Kawser Hossain2
1Department of Data Science, Bangabandhu Sheikh Mujibur Rahman Digital University, Bangladesh.
Data in brief
|August 27, 2024
概括
研究人员开发了一个新的孟加拉语数学方程数据集,以改善方程识别. 这一数据集有助于识别孟加拉文本中的数学运算和值,推进机器学习应用.
科学领域:
- 自然语言处理自然语言处理.
- 计算机科学 计算机科学
- 数学 数学 是一个数学.
背景情况:
- 方程识别对于开发数学系统至关重要.
- 孟加拉语数学方程识别的现有资源有限.
- 开发专门的数据集对于在特定语言中推进NLP任务至关重要.
研究的目的:
- 为孟加拉语数学方程识别引入一个新的数据集.
- 为在孟加拉语文中提供识别数学命题和方程的资源.
- 促进研究识别数学运算和数值的研究.
主要方法:
- 创建一个孟加拉语数学方程数据集,包含3430个观察.
- 在CSV格式中以"文本"和"方程"列构建数据集.
- 确保数据集包括常见的数学运算和数值.
主要成果:
- 现在可以获得3430个孟加拉语数学方程的独特数据集.
- 该数据集支持识别基本的算术运算和数值.
- 原始的CSV格式有助于与深度学习和机器学习模型的集成.
结论:
- 新的孟加拉语数学方程数据集显著推进了孟加拉语方程识别的研究.
- 这个资源可以适应各种机器学习任务,包括符号和值识别.
- 该数据集为孟加拉语的数学NLP未来工作提供了基础.
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