自然语言处理方法在国防预算分析中的应用

IF 0.7 Q3 ECONOMICS
Tetiana Zatonatska, Ganna Kharlamova, Vadym Pakholchuk, Alim Syzov
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引用次数: 0

摘要

向经济 5.0 转型非常重视人工智能技术在民用和军用领域的应用。本文旨在建立乌克兰国防部预算计划与战略目标和任务之间的关系模型。经典的预算分析方法通过 NLP 技术进行了扩展。分析对象为国防预算项目 2101020--确保乌克兰武装力量的活动、人员和部队的培训、人员、退伍军人及其家属以及退伍军人的医疗支持。在使用 Python 库和软件包的同时,还使用了 TF-IDF 或更先进的 NLP 方法。结果发现,一些目标之间存在语义相似性交叉。尽管缺乏数据,我们还是建立了概念验证机器学习模型,并证明了其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Natural Language Processing Methods Application in Defense Budget Analysis
Transferring to economy 5.0 makes a great emphasis on Artificial Intelligence technologies implementation in civil and military areas. The aim of the article is to model relation between the Ukrainian Ministry of Defense budget programs and strategic goals and tasks. The classical budget analysis methodology is extended with NLP technics. The analysis is performed for defense budget program 2101020 - Ensuring the activities of the Armed Forces of Ukraine, training of personnel and troops, medical support of personnel, military service veterans and their family members, and war veterans. Either TF-IDF or more advanced NLP methods are used along with Python libraries and packages. It is found that some goals intersect with each other by semantic similarity. Despite the lack of data, we build proof of concept machine learning model and proved its effectiveness.
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来源期刊
CiteScore
1.30
自引率
16.70%
发文量
20
审稿时长
30 weeks
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