@inproceedings{3afeb799256846d9b551ad2accc5ffd4,
title = "Co-clustering of time-evolving news story with transcript and keyframe",
abstract = "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.",
author = "Xiao Wu and Ngo, \{Chong Wah\} and Qing Li",
year = "2005",
month = dec,
day = "1",
doi = "10.1109/ICME.2005.1521374",
language = "English",
isbn = "0780393325",
series = "IEEE International Conference on Multimedia and Expo, ICME 2005",
pages = "117--120",
booktitle = "IEEE International Conference on Multimedia and Expo, ICME 2005",
note = "IEEE International Conference on Multimedia and Expo, ICME 2005 ; Conference date: 06-07-2005 Through 08-07-2005",
}