Paper Info
Title
Story segmentation of broadcast news in Arabic, Chinese and English using multi-window features
Abstract
The paper describes a maximum entropy based story segmentation system for Arabic, Chinese and English. In experiments with broadcast news data from TDT-3, TDT-4, and corpora collected in the DARPA GALE project we obtain a substantial performance gain using multiple overlapping windows for text-based features.
Year
DOI
Venue
2007
10.1145/1277741.1277867
SIGIR
Keywords
Field
DocType
text-based feature,multi-window feature,story segmentation system,multiple overlapping windows,substantial performance gain,darpa gale project,maximum entropy,broadcast news data
Broadcasting,Arabic,Segmentation,Computer science,Speech recognition,Natural language processing,Artificial intelligence,Principle of maximum entropy
Conference
Citations 
PageRank 
References 
1
0.35
5
Authors
2
Name
Order
Citations
PageRank
Martin Franz148353.56
Jian-ming Xu2193.10