标题:Event Detection in Multiple Webpages based on Comprehensive Dimension Matching and Co-occurrence Constraint
作者:Xu, Yuanzi; Li, Qingzhong; Yan, Zhongmin; Wang, Wei
作者机构:[Xu, Yuanzi; Li, Qingzhong; Yan, Zhongmin; Wang, Wei] Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Peoples R China.
通讯作者:Li, QZ
通讯作者地址:[Li, QZ]Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Peoples R China.
来源:APPLIED MATHEMATICS & INFORMATION SCIENCES
出版年:2014
卷:8
期:3
页码:1267-1276
DOI:10.12785/amis/080341
关键词:Event detection; comprehensive dimension matching; co-occurrence; constraint; extended evidence theory
摘要:Detecting various sentence-level events from multiple webpages can be important in finding knowledge. We propose an event detection method based on comprehensive dimension matching and co-occurrence constraint. First, we detect events from a single webpage by clustering co-reference sentence-level event mentions. These events are considered as co-occurrence events in every single webpage. Second, similar events from multiple webpages are clustered. The dimension matching method is used to aggregate event mentions. Different matchers measure different dimensions, and an extended evidence theory is proposed to allocate dynamic weight and combine dimension measurement results. We propose an event co-occurrence constraint to reduce match times and quantity of candidate matches events in the multiple webpages event-detection process to improve event cluster efficiency. The experiment results demonstrate that this method can detect various events and noticeably reduce the quantity of co-reference events.
收录类别:SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893089831&doi=10.12785%2famis%2f080341&partnerID=40&md5=525c786accb483e52d0e71ce56ae1d24
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