DocumentCode :
2449515
Title :
A Study for Sentence Ordering Based on Grey Model
Author :
Peng, Gongfu ; He, Yanxiang ; Zhang, Wei ; Xiong, Naixue ; Tian, Ye
Author_Institution :
Comput. Sch., Wuhan Univ., Wuhan, China
fYear :
2010
fDate :
6-10 Dec. 2010
Firstpage :
567
Lastpage :
572
Abstract :
This paper propose a method for sentence ordering in multi-document summarization task, which combine support vector machine (SVM) and Grey Model(GM). Firstly, the method train the SVM with sentences of source documents and predict sentences sequence of summary as primary dataset. Secondly, using Grey Model to process the primary dataset, and achieve the final sequence of summary sentences. Experiments on 100 summaries showed this method provide a much higher precision than probabilistic model in sentence ordering task.
Keywords :
document handling; grey systems; natural language processing; statistical analysis; SVM; grey model; multi-document summarization task; probabilistic model; sentence ordering task; support vector machine; Biological system modeling; Computers; Data models; Educational institutions; Feature extraction; Silicon; Support vector machines; Grey Model; Multi-document; Sentence ordering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Services Computing Conference (APSCC), 2010 IEEE Asia-Pacific
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-9396-8
Type :
conf
DOI :
10.1109/APSCC.2010.97
Filename :
5708622
Link To Document :
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