Records management system using deep learning

Provided is a record classification system using deep learning, which comprises: a legal database storing information on legal provisions information related to information disclosure by public institution; a record management database managing existing documents including legal provisions informati...

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Bibliographic Details
Main Authors HEO JUN SEOK, KIM YOUNG
Format Patent
LanguageEnglish
Korean
Published 28.09.2020
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Summary:Provided is a record classification system using deep learning, which comprises: a legal database storing information on legal provisions information related to information disclosure by public institution; a record management database managing existing documents including legal provisions information on the disclosure classification after the disclosure classification has been completed; a record management system providing an electronic document which needs the disclosure classification, wherein the electronic document includes the public institution name, the unit business name, the processing department name, the document title, and the document content; and a processing means receiving the existing document in which the disclosure classification has been completed from the record management database to generate first disclosure classification reference data through natural language processing, comparing and analyzing the first disclosure classification reference data with the electronic document transmitted from the record management system, and automatically classifying the disclosure, partial disclosure, and non-disclosure of the electronic document. 딥러닝을 이용한 기록물 분류 시스템은 공공기관별 정보공개 관련 법률조항정보를 저장하고 있는 법률 데이터베이스와, 공개구분이 완료되어 공개구분에 대한 법률조항정보를 포함하고 있는 기존문서를 관리하는 기록물 관리 데이터베이스와, 공개구분이 필요한 전자문서 - 공공기관명, 단위업무명, 처리과명, 문서제목 및 문서내용을 포함함 - 를 제공하는 기록물관리시스템과, 기록물 관리 데이터베이스로부터 공개구분이 완료된 기존문서를 제공받아 자연어 처리를 통해 제1 공개구분 기준데이터를 생성하고, 제1 공개구분 기준데이터와 상기 기록물관리시스템으로부터 전달되는 전자문서를 비교분석하여 상기 전자문서의 공개, 부분공개 및 비공개 여부를 자동 분류하는 공개구분 처리수단을 포함하는 것을 특징으로 한다.
Bibliography:Application Number: KR20190030397