BidCorpus:为公共采购提供多方面的学习数据集
Weslley Lima1, Victor Silva1, Jasson Silva1
1Federal University of Piauí. Campus Universitário Ministro Petrônio Portella. Teresina, Piauí, Brazil.
Data in brief
|January 10, 2025
概括
我们创建了BidCorpus,这是一个用于分析公共采购文件的新数据集. 这一数据集有助于自动检测招标公告中的欺诈行为,提高公共管理的效率和透明度.
科学领域:
- 信息科学 信息科学 信息科学
- 公共管理 公共管理
- 计算机科学 计算机科学
背景情况:
- 数字化转型提高了公共采购的效率,透明度和竞争.
- 在公共管理中,数据分析和监督的自动化至关重要.
- 手动分析非结构化采购文件耗时且效率低下.
研究的目的:
- 介绍BidCorpus,这是一个关于公共采购招标公告的全面数据集.
- 促进公共采购文件的自动化分析和欺诈检测.
- 为公共采购领域的研究人员提供宝贵的资源.
主要方法:
- 收集了数千份巴西公共采购招标公告.
- 利用弱监督,手动标签和基于BERT的数据注释模型.
- 在注释数据集上训练和评估机器学习模型.
主要成果:
- 在BidCorpus上训练的模型在各种实验中实现了超过80%的准确性.
- 这些模型证明了针对旨在逃避欺诈检测的故意修改的稳定性.
- 开发并验证了用于分析公共采购数据的机器学习模型.
结论:
- BidCorpus是推动公共采购研究的宝贵资源.
- 对招标公告的自动化分析可以显著提高欺诈检测和效率.
- 公开可用的资源支持数字公共采购领域的进一步发展.
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