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ICMCS
2005
IEEE

Co-Clustering of Time-Evolving News Story with Transcript and Keyframe

10 years 6 months ago
Co-Clustering of Time-Evolving News Story with Transcript and Keyframe
This paper presents techniques in clustering the sametopic news stories according to event themes. We model the relationship of stories with textual and visual concepts under the representation of bipartite graph. The textual and visual concepts are extracted respectively from speech transcripts and keyframes. Co-clustering algorithm is employed to exploit the duality of stories and textual-visual concepts based on spectral graph partitioning. Experimental results on TRECVID-2004 corpus show that the co-clustering of news stories with textual-visual concepts is significantly better than the co-clustering with either textual or visual concept alone.
Xiao Wu, Chong-Wah Ngo, Qing Li
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICMCS
Authors Xiao Wu, Chong-Wah Ngo, Qing Li
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