Earticle

초록

영어

Expectation and interest about e-CRM are rising for more efficient customer management in on-line including electronic commerce. The decision-making tree can be used usefully as the data mining technology for e-CRM. In this paper, the representative decision making techniques, CART, C4.5, CHAID analyzed the differences in personalization point of view with actuality customer data through an experiment. With these analysis data, it is proposed a new decision-making tree system that has big advantage in personalization techniques. Through new system, it can get following advantage. First, it can form superior model more qualitatively in personalization by adding individual's weight value. Second it can supply information personalized more to customer. Third, it can have high position about customer's loyalty than other site of similar types of business. Fourth, it can reduce expense that cost marketing and decision-making. Fifth, it becomes possible that know that customer through smooth communication with customer who use personalized service wants and make from goods or service's quality to more worth thing.

목차

Abstract
 1. 서론
 2. 의사결정나무 알고리즘
  2.1 CHAID (Chi-squard Automatic Interaction Detection)
  2.2 CART
  2.3 C4.5
 3. 알고리즘의 유효성 분석
  3.1 전자상거래 관점에서의 비교
  3.2 개인화 관점에서의 비교
 4. 제안 시스템
  4.1 기본 개념
  4.2 제안 시스템의 효과
  4.3 e-CRM의 효과
  4.4 제안 시스템의 실험평가
 5. 결론
 6. 참고문헌

키워드

저자

• 양정희 [ Yang Jeong Hoe | 인덕대학 산업시스템경영과 ]
• 한서정 [ Han Seo Jeong | 호서대학교 디지털비즈니스학부 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  대한안전경영과학회지 [Journal of Korea Safety Management & Science]

• 간기

  계간

• pISSN

  1229-6783

• eISSN

  2288-1484

• 수록기간

  1999~2025

• 십진분류

  KDC 530 DDC 620