Natural Language Processing Methods Application in Defense Budget Analysis

Abstract

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.

Keywords

• natural language processing
• word embedding
• defense budget
• defense expenditures
• transparency