메뉴 건너뛰기
소속 기관 / 학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
고객센터 ENG
주제분류

논문 기본 정보

저자정보
(University of Toronto) (서울대학교) (서울대학교)
저널정보
한국멀티미디어학회 멀티미디어학회논문지 멀티미디어학회논문지 제19권 제8호
오류 신고하기

피인용 1

검색

    초록·키워드

    With the spread of social media and mobile devices, people spend more time on online than ever before. As more people participate in various online activities, much research has been conducted on how to make use of the time effectively and productively. In this paper, we propose two methods which can be used to extract highlights and make searchable media indexes using online social data. For highlight extraction, we collected the comments from the online baseball broadcasting website. We adopted peak-finding algorithm to analyze the frequency of comments uploaded on the comments section of the website. For each indexes, we collected postings from soap opera forums provided by a popular web service called DCInside. We extracted all the instances when a character’s name is mentioned in postings users upload after watching TV, which can be used to create indexes when the character appears on screen for the given episode of the soap opera The evaluation results shows the possibility of the crowdsourcing-based media interaction for both highlight extraction and index building.

    최근 본 자료 전체보기

      UCI(KEPA) : I410-ECN-0101-2017-004-001136726