확률 그래프 모형 기반의 트랜잭션 데이터 분석 방법론

Abstract

Recently, transaction data is accumulated everywhere such as bank and IT company. Association analysis methods are usually applied to analyze transaction data, but the methods have several problems. For example, these methods only consider one-way relations among items and cannot reflect domain knowledge to analysis process. In order to overcome defect of association analysis methods, we suggest a transaction data analysis method based on probabilistic graphical model (PGM) in this study. The method we suggest has several advantages as compared with association analysis methods. For example, this method has a high flexibility, so it can give a solution to various probability problems regarding the transaction data and can consider various relationships among items.