Recurrent Neural Network를 활용한 서비스 이벤트 관계 분석에 관한 연구

• 영문명: The Study of Service Event Relation Analysis Using Recurrent Neural Network
• 발행기관: 한국IT서비스학회
• 저자명: 전우성(Woosung Jeon) 박영석(Youngsuk Park) 최정일(Jeongil Choi)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제17권 제4호, 75~83쪽, 전체 9쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2018.12.31

영문 초록

Enterprises need to monitor systems for reliable IT service operations to quickly detect and respond to events affecting the service, thereby preventing failures. Events in non-critical systems can be seen as a precursor to critical system incidents. Therefore, event relationship analysis in the operation of IT services can proactively recognize and prevent faults by identifying non-critical events and their relationships with incidents. This study used the Recurrent Neural Network and Long Short Term Memory techniques to create a model to analyze event relationships in a system and to verify which models are suitable for analyzing event relationships. Verification has shown that both models are capable of analyzing event relationships and that RNN models are more suitable than LSTM models. Based on the pattern of events occurring, this model is expected to support the prediction of the next occurrence of events and help identify the root cause of incidents to help prevent failures and improve the quality of IT services.

목차

1. 서 론

2. 이론적 배경

3. 이벤트 분석 방안

4. 이벤트 관계 분석

5. 결 론

키워드

Event Correlation Analysis IT Service Long Short Term Memory Recurrent Neural Network Root Cause Analysis