Title :
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
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;
Conference_Titel :
System Science, Engineering Design and Manufacturing Informatization (ICSEM), 2011 International Conference on
Conference_Location :
Guiyang
Print_ISBN :
978-1-4577-0247-1
DOI :
10.1109/ICSSEM.2011.6081195
