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Journal Article
Extracting Events from Web Documents for Social Media Monitoring Using Structured SVM
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- Authors
- Yoonjae CHOI, Pum-Mo RYU, Hyunki KIM, Changki LEE
- Issue Date
- 2013-06
- Citation
- IEICE Transactions on Information and Systems, v.E96.D, no.6, pp.1410-1414
- ISSN
- 0916-8532
- Publisher
- 일본, 전자정보통신학회 (IEICE)
- Language
- English
- Type
- Journal Article
- Abstract
- 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 Keywords
- ART classifier, Event extraction, Event prediction, Information and communication, Relation Extraction, Social Media Monitoring, Social event, Structured SVM, Structured support, Support VectorMachine(SVM), Web documents