[1]CHEN Xiaoqi,XIE Zhenping,LIU Yuan.News event detection driven by incremental sampling clustering[J].CAAI Transactions on Intelligent Systems,2020,15(6):1175-1184.[doi:10.11992/tis.201912037]
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News event detection driven by incremental sampling clustering

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 15 Number of periods: 2020 6 Page number: 1175-1184 Column: 学术论文—自然语言处理与理解 Public date: 2020-11-05
Title:
News event detection driven by incremental sampling clustering
Author(s):
CHEN Xiaoqi1; 2;  XIE Zhenping1; 2;  LIU Yuan1; 2
1. School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China;
2. Jiangsu Key Laboratory of Media Design and Software Technology, Jiangnan University, Wuxi 214122, China
Keywords:
news flow data; event detection; representative news; incremental sampling; information supporting degree; affinity propagation; event network; hierarchical clustering
CLC:
TP391
DOI:
10.11992/tis.201912037
Abstract:
For obtaining better performance of event detection and representative news extraction, an integrated analysis method of event detection and representation is proposed by introducing the sampling clustering strategy on news documents. For a given news flow data, first, we present two-weight definitions on the relationships between news and events by introducing an information supporting degree concept and then construct a one-way event content support network on the whole time flow using the iterative algorithm of double-layer nearest affinity propagation to realize layer-by-layer incremental sampling of representative news. Furthermore, overall news clustering was performed by using the maximum similarity division strategy. According to our experimental results, compared with existing related methods, the new method has significant computational efficiency for processing large-scale news flow data. It can extract the most representative news from the news flow and obtain better clustering quality of news documents. Its hot event detection results are highly consistent with the major news selected by the authority.
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