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      머신러닝을 이용한 세금 계정과목 분류 = Taxation Analysis Using Machine Learning

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      https://www.riss.kr/link?id=A106260564

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      다국어 초록 (Multilingual Abstract)

      Data mining techniques can also be used to increase the efficiency of production in the tax sector, which requires professional skills. As tax-related computerization was carried out, large amounts of data were accumulated, creating a good environment...

      Data mining techniques can also be used to increase the efficiency of production in the tax sector, which requires professional skills. As tax-related computerization was carried out, large amounts of data were accumulated, creating a good environment for data mining. In this paper, we have developed a system that can help tax accountant who have existing professional abilities by using data mining techniques on accumulated tax related data. The data mining technique used is random forest and improved by using f1-score. Using the implemented system, data accumulated over two years was learned, showing high accuracy at prediction.

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      참고문헌 (Reference)

      1 J. Peters, "Uncertainty propagation in vegetation distribution models based on ensemble classifiers" 220 : 791-804, 2009

      2 Sasaki Y, "The truth of the F-measure Teach" 1-5, 2007

      3 T.K. Ho, "The random subspace method for constructing decision forests" 20 (20): 832-844, 1998

      4 L.Breiman, "Randomforests" 45 : 5-32, 2001

      5 M.M. Crawford, "Random forests of binary hierarchical classifiers for analysis of hyperspectral data" IEEE 337-345, 2004

      6 J. Peters, "Random forests as a tool for ecohydrological distribution modelling" 207 : 304-318, 2007

      7 Verikas A, "Mining data with random forests: a survey and results of new tests" 44 : 330-349, 2011

      8 Lakshmi, R. D., "Machine Learning Approach for Taxation Analysis using Classification Techniques" 12 (12): 2011

      9 J. Ham, "Investigation of the random forest framework for classification of hyperspectral data" 43 (43): 492-501, 2005

      10 G. Nimrod, "Identification of DNA-binding proteins using structural, electrostatic and evolutionary features" 387 (387): 1040-1053, 2009

      1 J. Peters, "Uncertainty propagation in vegetation distribution models based on ensemble classifiers" 220 : 791-804, 2009

      2 Sasaki Y, "The truth of the F-measure Teach" 1-5, 2007

      3 T.K. Ho, "The random subspace method for constructing decision forests" 20 (20): 832-844, 1998

      4 L.Breiman, "Randomforests" 45 : 5-32, 2001

      5 M.M. Crawford, "Random forests of binary hierarchical classifiers for analysis of hyperspectral data" IEEE 337-345, 2004

      6 J. Peters, "Random forests as a tool for ecohydrological distribution modelling" 207 : 304-318, 2007

      7 Verikas A, "Mining data with random forests: a survey and results of new tests" 44 : 330-349, 2011

      8 Lakshmi, R. D., "Machine Learning Approach for Taxation Analysis using Classification Techniques" 12 (12): 2011

      9 J. Ham, "Investigation of the random forest framework for classification of hyperspectral data" 43 (43): 492-501, 2005

      10 G. Nimrod, "Identification of DNA-binding proteins using structural, electrostatic and evolutionary features" 387 (387): 1040-1053, 2009

      11 H.T. Chen, "ECCV 2006, Part IV, Lecture Notes in Computer Science, vol. 3954" Springer-Verlag 373-385, 2006

      12 G. Biau, "Consistency of random forests and other averaging classifiers" 9 : 2015-2033, 2008

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2027 평가예정 재인증평가 신청대상 (재인증)
      2021-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2019-01-01 평가 등재학술지 유지 (계속평가) KCI등재
      2016-01-01 평가 등재학술지 유지 (계속평가) KCI등재
      2012-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2010-03-25 학회명변경 한글명 : 한국반도체및디스플레이장비학회 -> 한국반도체디스플레이기술학회
      영문명 : The Korean Society of Semiconductor & Display Equipment Technology -> The Korean Society of Semiconductor & Display Technology
      KCI등재
      2010-03-25 학술지명변경 한글명 : 반도체및디스플레이장비학회지 -> 반도체디스플레이기술학회지
      외국어명 : Journal of the Semiconductor and Display Equipment Technology -> Journal of the Semiconductor & Display Technology
      KCI등재
      2009-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2008-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2006-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.29 0.29 0.26
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.21 0.18 0.217 0.02
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