An approach for discovering Multilingual news events and term association from the Web

Author

Chen, Hang ; Wei, Ronghao

Author_Institution

Coll. of Continuing Educ., GuiZhou Univ., Guiyang, China

Volume

1

fYear

2011

fDate

22-23 Oct. 2011

Firstpage

239

Lastpage

244

Abstract

We have investigated an approach for automatically discovering news events from Web online news downloaded from different sites of different languages. The story content is analyzed. Unsupervised learning is conducted to discover events. From the comparable news stories in the events, statistical analysis of term co-occurrence is developed for mining bilingual term associations. We have conducted some experiments to evaluate our approach on discovering events and term associations. According to the result of the experiment, the approach is a effective way for the discovering Multilingual news events and term association from the web.

Keywords

Internet; data mining; statistical analysis; unsupervised learning; Web online news; bilingual term association mining; multilingual news event discovery; statistical analysis; term association discovery; term co-occurrence analysis; unsupervised learning; Encoding; Weapons; information retrieval; term association; text mining;

fLanguage

English

Publisher

ieee

Conference_Titel

System Science, Engineering Design and Manufacturing Informatization (ICSEM), 2011 International Conference on

Conference_Location

Guiyang

Print_ISBN

978-1-4577-0247-1

Type

conf

DOI

10.1109/ICSSEM.2011.6081195

Filename

6081195