DocumentCode
2382930
Title
On-line event detection from web news stream
Author
Fu, Yan ; Zhou, Ming-quan ; Wang, Xue-song ; Luan, Hua
Author_Institution
Coll. of Inf. Sci. & Technol., Beijing Normal Univ., Beijing, China
fYear
2010
fDate
1-3 Dec. 2010
Firstpage
105
Lastpage
110
Abstract
In order to improve detection efficiency of on-line web news stream, we propose a new method to accomplish detection task with window-adding, named entity recognition and suffix tree clustering. In our method, we make full use of informative elements of news stream(such as date, place, person and so on) to help detection process, and this method decreases text similarity computation greatly. Experimental results show that our method improves on-line event detection performance, without sacrificing detection precision.
Keywords
Internet; pattern clustering; publishing; text analysis; trees (mathematics); Web news stream; detection efficiency; detection precision; detection process; detection task; informative elements; named entity recognition; online event detection; suffix tree clustering; text similarity computation; window-adding; named entity recognition; on-line event detection; suffix-tree clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Pervasive Computing and Applications (ICPCA), 2010 5th International Conference on
Conference_Location
Maribor
Print_ISBN
978-1-4244-9144-5
Type
conf
DOI
10.1109/ICPCA.2010.5704083
Filename
5704083
Link To Document