NEWS STORY CLUSTERING WITH FISHER EMBEDDING

被引：0
|
作者：
Chu, Wei-Ta [1 ]
Hsu, Han-Nung [1 ]
机构：
[1] Natl Chung Cheng Univ, Chiayi, Taiwan
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING PROCEEDINGS | 2016年
关键词：
Fisher vector; news story clustering; what and how aspects;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
An automatic news story clustering system is presented to facilitate efficient news browsing and summarization. We describe news content by considering both what objects appear and how these objects move in news stories. With Fisher embedding, we respectively encode local features, semantics features, and dense trajectories as Fisher vectors, based on which similarity between news stories can be well evaluated and thus better clustering performance can be obtained. We verify the effectiveness of Fisher encoding, and further show that motion-based features are more effective than appearancebased features through feature analysis.
引用
收藏
页码：1175 / 1178
页数：4
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