Earticle

초록

영어

In order to provide personalized knowledge recommendation services, most web portals for organizational knowledge management use category or keyword information that portal users explicitly express interests in. However, it is usually difficult to collect correct preference data for all users with this approach, and, moreover, users' preferences may easily change over time, which results in outdated user profiles and impaired recommendation quality. In order to address this problem, this paper suggests knowledge recommendation methods for portals using user profiles that are automatically constructed from users' activities such as posting or uploading of articles and documents. The result of our experiment shows that the proposed method can provide equivalent performance with the manual category or keyword selection method.

목차

Abstract
 1. 서론
 2. 개인화된 지식제공 방안과 지식포탈
 3. 지식포탈에서의 개인화된 지식제공 방안
  3.1 자동 분류기반 방식
  3.2 벡터 공간 모델 방안
 4. 개인화 지식제공 방안 비교 실험
  4.1 실험 환경 및 과정
  4.2 실험결과
 5. 토의 및 결론
 참고문헌

키워드

저자

• 이홍주 [ Hong Joo Lee | 한국과학기술원 테크노경영대학원 박사과정 ] 주저자
• 김종우 [ Jong Woo Kim | 한양대학교 경영대학 경영학부 부교수 ] 교신저자
• 김광래 [ Gwang Rae Kim | 충남대학교 통계학과 박사과정 ]
• 안형준 [ Hyung Jun Ahn | Lecturer, Management Systems, Waikato Management School, University of Waikato ]
• 권철현 [ Chul Hyun Kwon | 삼성 SDS Biz 컨설팅센터 선임컨설턴트 ]
• 박성주 [ Sung Joo Park | 한국과학기술원 테크노경영대학원 교수 ]

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