DocumentCode :
2117823
Title :
The Retrieval of Important News Stories by Influence Propagation among Communities and Categories
Author :
Yu-Fan Lin ; Hung-Yu Kao
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Volume :
1
fYear :
2012
fDate :
4-7 Dec. 2012
Firstpage :
32
Lastpage :
39
Abstract :
Nowadays, people receive information of the news stories not only from newspapers but also from online news websites. They search important news stories in order to know what happen today. However, it is hard to browse all the news stories published on a day. It is necessary to identify which news stories are more newsworthy on the specific day. In this paper, we investigate how to automatically identify the importance of news stories for different news categories on a specific day by utilizing the influence propagation among communities and news categories. In particular, we build an influence propagation model which consists of three features: category relevance, bloggers´ attention and bursty influence. Based on this influence propagation model, we propose a Cross-Category Social Influence Propagation (C-SIP) approach for scoring the importance of news stories on a specific day. We evaluate our approach by using the judgment of Story Ranking Task in TREC 2010 Blog Track. The experiment shows our approach attains a prominent performance in the retrieval of important news stories and gets 9.94% improvement over the best performance of participating systems in TREC 2010 Blog Track.
Keywords :
Web sites; information retrieval; bursty influence; category relevance; cross category social influence propagation; important news stories retrieval; influence propagation model; news category; online news Web sites; story ranking task; Blog; Influence propagation; Information Bursty; News story distillation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on
Conference_Location :
Macau
Print_ISBN :
978-1-4673-6057-9
Type :
conf
DOI :
10.1109/WI-IAT.2012.236
Filename :
6511862
Link To Document :
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