Earticle

초록

영어

Most of hospitals, especially small-scale hospitals, have tried to get customers through the Internet as what companies have done recently. There are various attempts that increase visits to one’s web-site in plastic surgery hospitals. However, in plastic surgery, there have been few studies on which an attribute contributes to increase the number of web-site visit. In order to derive the important attributes on the number of visit, we compared functional attributes of 30 high-visit plastic surgery web-sites with those of 30 low-visit web-sites using statistical and data mining methods. For analysis, three methods have conducted including Multiple Discriminant Analysis (statistical method), Decision Trees (data mining method), and Artificial Neural Network (data mining method). Furthermore, results of each method have been evaluated one another. The result of this study shows that a few attributes like ‘Simulating cyber plastic surgery program’, ‘recommendation of information’ explain the number of the visitors between high and low visit web-site. The methodology employed in this study provides an efficient way of improving satisfaction of visitors of plastic surgery website.

목차

Abstract
 1. 서론
 2. 관련 연구
 3. 조사 및 분석방법
  3.1 조사대상
  3.2. 조사내용
  3.3 조사 및 분석방법
 4. 결과
  4.1 데이터 전처리(data preprocessing) 및 기술 통계량
  4.2 다중 판별 함수(Multiple Discriminant Analysis)분석 결과
  4.3 의사결정나무(Decision trees) 분석결과
  4.4 인공신경망(Artificial Neural Network) 분석 결과
  4.5 두 집단 구분 웹 사이트 속성
 5. 결론
 참고문헌

키워드

저자

• 조영빈 [ Yeong Bin Cho | 건국대학교 사회과학대학 경영학과 ] 교신저자
• 안성현 [ Seong Hyeon An | 연세대학교 의과대학 의학공학교실 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  JITAM [Journal of Information Technology Applications and Management]

• 간기

  격월간

• pISSN

  1598-6284

• eISSN

  2508-1209

• 수록기간

  1999~2026

• 십진분류

  KDC 005 DDC 005