Title :
Combination of Features for Vietnamese News Multi-document Summarization
Author :
Van-Giau Ung;An-Vinh Luong;Nhi-Thao Tran;Minh-Quoc Nghiem
Author_Institution :
Fac. of Inf. Technol., Ho Chi Minh City Univ. of Sci., Ho Chi Minh City, Vietnam
Abstract :
The aim of multi-document summarization is to produce an abridged version which contains important information from a set of documents on the same topic. This paper describes an approach that incorporates a set of features at word and sentence level to extract important sentences from input documents for Vietnamese news multi-document summarization system. Then, the summaries are evaluated automatically by using the ROUGE measure. The obtained result indicates that this approach produces good summaries and is appropriate for Vietnamese as well as languages limited linguistic resources.
Keywords :
"Feature extraction","Pragmatics","Redundancy","Cities and towns","Semantics","Supervised learning","Unsupervised learning"
Conference_Titel :
Knowledge and Systems Engineering (KSE), 2015 Seventh International Conference on
DOI :
10.1109/KSE.2015.71