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Methods for screening time series data according to data quality and statistical status
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품질 및 조건 기반 시계열 데이터 선별 활용 방법

논문 기본 정보

Type
Proceeding
Author
JaeWon Moon (한국전자기술연구원) MiSeon Yu (한국전자기술연구원) SeungTaek Oh (한국전자기술연구원) SeungWoo Kum (한국전자기술연구원) JiSoo Hwang (한국전자기술연구원) JiHoon Lee (한국전자기술연구원)
Journal
The Korean Society Of Computer And Information Proceedings of the Korean Society of Computer Information Conference Vol.30 No.1
Published
2022.1
Pages
399 - 402 (4page)

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Methods for screening time series data according to data quality and statistical status
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본 논문에서는 불완전한 시계열 데이터를 활용하기 전 데이터를 선별하여 활용하는 방법을 소개한다. 시계열 데이터의 품질은 수집 네트워크와 수집 기기의 시간적 변화와 같은 가변적 상황에 의존적이므로 불규칙적으로 이상 혹은 누락 데이터가 발생한다. 이때 에러를 포함하였다는 이유로 일괄적으로 데이터를 제거하여 활용하지 않거나, 혹은 누락 데이터의 구간을 조건 없이 복원하여 활용한다면 원하지 않는 결과를 초래할 수 있다. 제안하는 방법은 시계열 데이터의 구간에 대한 누락 데이터의 통계적 정보를 축출하고 이에 기반하여 활용 목적과 활용 가능한 품질의 기준에 부합하지 않는다면 활용 불가능한 데이터라고 판별하고 미리 분석 등의 데이터 활용 시 자동 제외하는 구조를 제안하고 실험하였다. 제안하는 방법은 활용 목적과 상황에 적응적으로 누락 값을 포함하는 데이터의 빠른 활용 판단이 가능하며 보다 나은 분석 결과를 얻을 수 있다.
#시계열 데이터 (Timeseries data) #누락 데이터 보완 (Missing Data Imputation) #적응적 데이터 처리 (Adaptive data processing)

Contents

요약
I. Introduction
II. 누락 데이터 처리
III. 데이터 선별 보완 방법
IV. 결론
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