전자메일 자동관리 시스템을 위한 전자메일 분류기의 개발

• 영문명: Development of e-Mail Classifiers for e-Mail Response Management Systems
• 발행기관: 한국IT서비스학회
• 저자명: 김국표(Kuk Pyo Kim) 권영식(Young S. Kwon)
• 간행물 정보: 『한국IT서비스학회지』한국SI학회지 제2권 제2호, 87~95쪽, 전체 9쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2003.11.01

영문 초록

With the increasing proliferation of World Wide Web, electronic mail systems have become very widely used communication tools. Researches on e-mail classification have been very important in that e-mail classification system is a major engine for e-mail response management systems which mine unstructured e-mail messages and automatically categorize them. In this research we develop e-mail classifiers for e-mail Response Management Systems (ERMS) using naive bayesian learning and centroid-based classification. We analyze which method performs better under which conditions, comparing classification accuracies which may depend on the structure, the size of training data set and number of classes, using the different data set of an on-line shopping mall and a credit card company. The developed e-mail classifers have been successfully implemented in practice. The experimental results show that naive bayesian learning performs better, while centroid-based classification is more robust in terms of classification accuracy.

목차

Abstract

1. 서 론

2. 선행 연구

3. 구현된 두 가지 분류기

4. 실험과 결과분석

5. 결 론

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