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

조세심판 문서 검색 효율 향상 모델에 관한 연구

  • 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)
  • 이후영 (공주대학교 컴퓨터공학과) ;
  • 박구락 (공주대학교 컴퓨터공학부) ;
  • 김동현 (공주대학교 컴퓨터공학과)
  • Received : 2019.05.01
  • Accepted : 2019.06.20
  • Published : 2019.06.28

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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Fig. 1. Distributed Momory(DM) Model

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Fig. 2. Distributed Bag of Words(DBOW) Model

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Fig. 3. Flow of Natural Language Processing

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Fig. 4. System Configuration

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Fig. 5. Structure of Judgment Document

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FIg. 6. Visualization of Analytical Data

Table 1. Extract the Top 10 Words

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Table 2. Most Words and Highly Similar Word List

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Table 3. Change in Cosine Similarity

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