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http://dx.doi.org/10.15207/JKCS.2019.10.6.041

A Study on the Improvement Model of Document Retrieval Efficiency of Tax Judgment  

Lee, Hoo-Young (Dept. of Computer Engineering, Kongju National University)
Park, Koo-Rack (Dept. of Computer Science & Engineering, Kongju National University)
Kim, Dong-Hyun (Dept. of Computer Engineering, Kongju National University)
Publication Information
Journal of the Korea Convergence Society / v.10, no.6, 2019 , pp. 41-47 More about this Journal
Abstract
It is very important to search for and obtain an example of a similar judgment in case of court judgment. The existing judge's document search uses a method of searching through key-words entered by the user. However, if it is necessary to input an accurate keyword and the keyword is unknown, it is impossible to search for the necessary document. In addition, the detected document may have different contents. In this paper, we want to improve the effectiveness of the method of vectorizing a document into a three-dimensional space, calculating cosine similarity, and searching close documents in order to search an accurate judge's example. Therefore, after analyzing the similarity of words used in the judge's example, a method is provided for extracting the mode and inserting it into the text of the text, thereby providing a method for improving the cosine similarity of the document to be retrieved. It is hoped that users will be able to provide a fast, accurate search trying to find an example of a tax-related judge through the proposed model.
Keywords
Convergence; Tax Cases; Similar Documents; NLP; Word Embedding;
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Times Cited By KSCI : 6  (Citation Analysis)
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