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http://dx.doi.org/10.14400/JDC.2021.19.9.181

Tax Judgment Analysis and Prediction using NLP and BiLSTM  

Lee, Yeong-Keun (Dept. of Computer Engineering, Kongju National University)
Park, Koo-Rack (Dept. of Computer Science & Engineering, Kongju National University)
Lee, Hoo-Young (Dept. of Computer Engineering, Kongju National University)
Publication Information
Journal of Digital Convergence / v.19, no.9, 2021 , pp. 181-188 More about this Journal
Abstract
Research and importance of legal services applied with AI so that it can be easily understood and predictable in difficult legal fields is increasing. In this study, based on the decision of the Tax Tribunal in the field of tax law, a model was built through self-learning through information collection and data processing, and the prediction results were answered to the user's query and the accuracy was verified. The proposed model collects information on tax decisions and extracts useful data through web crawling, and generates word vectors by applying Word2Vec's Fast Text algorithm to the optimized output through NLP. 11,103 cases of information were collected and classified from 2017 to 2019, and verified with 70% accuracy. It can be useful in various legal systems and prior research to be more efficient application.
Keywords
Artificial Intelligence; Legal System; Tax Tribunal; Word2Vec; BiLSTM; NLP;
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