상세정보
학술지
Extracting Events from Web Documents for Social Media Monitoring Using Structured SVM
- 발행일
- 201306
- 출처
- IEICE Transactions on Information and Systems, v.E96.D no.6, pp.1410-1414
- ISSN
- 0916-8532
- 출판사
- 일본, 전자정보통신학회 (IEICE)
- 협약과제
- 13VS1200, 웹 인텔리전스를 위한 웹 폭증 데이터 분석형 리스닝 플랫폼용 소셜웹 이슈 탐지-모니터링 및 예측 원천 기술 개발, 김현기
- 초록
- Event extraction is vital to social media monitoring and social event prediction. In this paper, we propose a method for social event extraction from web documents by identifying binary relations between named entities. There have been many studies on relation extraction, but their aims were mostly academic. For practical application, we try to identify 130 relation types that comprise 31 predefined event types, which address business and public issues. We use structured Support VectorMachine, the state of the art classifier to capture relations. We apply our method on news, blogs and tweets collected from the Internet and discuss the results. Copyright © 2013 The Institute of Electronics, Information and Communication Engineers.
- KSP 제안 키워드
- ART classifier, Binary relations, Event Prediction, Event extraction, Information and communication, Relation extraction, Social Events, Social Media Monitoring, Structured support, Support VectorMachine(SVM), Web Documents