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一个多学科多模拟对齐的数据集,用于学术数据处理.

Haitao Song1,2,3,4, Hongyi Xu1, Zikai Wang5,6,7

  • 1Shanghai Artificial Intelligence Research Institute Co., Ltd., Shanghai, 200240, China.

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|January 29, 2025
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概括
此摘要是机器生成的。

一个新的多式调整数据集 (MMAD) 用于学术数据处理包括超过110万学术文章与调整的文本和图像. 这一数据集通过使新的分析成为可能,推动了科学计量学和文献计量学方面的研究.

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科学领域:

  • 图书统计学 图书统计学
  • 科学测量公司的科学测量.
  • 数据科学数据科学数据科学

背景情况:

  • 学术数据处理在很大程度上依赖于scientometrics和bibliometrics中的文本数据.
  • 现有的数据集忽视了学术文章中的视觉元素的重要性.
  • 需要全面的数据集,整合文本和视觉信息.

研究的目的:

  • 引入一个新的,多学科的多式调整数据集 (MMAD) 用于学术数据处理.
  • 通过整合视觉数据,提高趋势分析和引用建议等领域的研究能力.
  • 在学术数据分析中为新的研究途径提供基础.

主要方法:

  • 汇编了超过110万篇同行评审学术文章的数据集.
  • 集成文本与对齐的视觉元素和相关的元数据.
  • 开发了一种基于语言模型的质量验证方法,使用特定提示来评估文本对视觉对齐的准确性.
  • 通过比较国家/地区分布与SCImago基准来评估数据集的代表性.

主要成果:

  • 多式调整数据集 (MMAD) 包含超过110万篇学术文章,其中包含了调整的文本和视觉效果.
  • 使用语言模型的新型验证方法证明了对文本与视觉对齐的有效质量控制.
  • 根据已建立的基准来评估MMAD的代表性.

结论:

  • 引入MMAD解决了现有数据集的差距,通过结合对齐的视觉元素.
  • MMAD促进了先进的学术数据处理,使自动化标题生成和图形趋势分析的新研究成为可能.
  • 这一数据集为科学计量学和参考计量学未来的进步提供了良好的基础.