Title :
News event summarization complemented by micropoints
Author :
Pingping Lin ; Rong Xiao ; Yan Zhang
Author_Institution :
Dept. of Machine Intell., Peking Univ., Beijing, China
Abstract :
In this paper, we propose a framework to produce comprehensive summarization of news event complemented by microblog. Given a basic summary extracted from traditional news articles, we extract micropoints from microblog to complement it. A micropoint is a micro-viewpoint composed of a few sentences from several relevant microblog tweets. We first filter microblog tweets and get candidate ones according to a combination of the degree of relevance and complementarity. Then we extract micropoints through tweet clustering, scattering and micropoint rebuilding. The last step - micropoint selection is based on three criteria, which guarantee high informativeness, popularity and conciseness. Experiments conducted on real data demonstrate a good coverage and content coherence.
Keywords :
Web sites; feature extraction; feature selection; information filtering; pattern clustering; relevance feedback; complementarity degree; microblog tweet filtering; micropoint extraction; micropoint rebuilding; micropoint selection; news event summarization; relevance degree; tweet clustering; tweet scattering; Clustering algorithms; Coherence; Data mining; Manuals; Mathematical model; Social network services;
Conference_Titel :
Data Engineering Workshops (ICDEW), 2015 31st IEEE International Conference on
Conference_Location :
Seoul
DOI :
10.1109/ICDEW.2015.7129575
