TY - GEN
T1 - Co-clustering of time-evolving news story with transcript and keyframe
AU - Wu, Xiao
AU - Ngo, Chong-Wah
AU - Li, Qing
PY - 2005
Y1 - 2005
N2 - 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. © 2005 IEEE.
AB - 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. © 2005 IEEE.
UR - http://www.scopus.com/inward/record.url?scp=33750539707&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-33750539707&origin=recordpage
U2 - 10.1109/ICME.2005.1521374
DO - 10.1109/ICME.2005.1521374
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 0780393325
SN - 9780780393325
VL - 2005
SP - 117
EP - 120
BT - IEEE International Conference on Multimedia and Expo, ICME 2005
T2 - IEEE International Conference on Multimedia and Expo, ICME 2005
Y2 - 6 July 2005 through 8 July 2005
ER -