DocumentCode :
3210747
Title :
Multi-document Relationship Model for a same subject and its application in automatic summarization
Author :
Bai Hao ; Zhou De-xiang
Author_Institution :
Sch. of Comput. Sci. & Technol., Henan Univ. of Technol., Zhengzhou, China
Volume :
2
fYear :
2010
fDate :
13-14 Sept. 2010
Firstpage :
20
Lastpage :
23
Abstract :
In this paper, we proposed Multi-document Relationship Model for a same subject and applicated it in automatic summarization. By using the relationship between text units in different level and information of time and sequence of event contained into document set, this model fuse many documents to extract summarization automatically under not reducing the information in original documents. This model simplified the traditional model presented by cross structure theory and simultaneously, replenish the evolution and distribution information of subject which lacked in information fusion. This paper gives some algorithm about construction of the model, information fusion for multi-document and summarization extraction and so on. Experiment results implied that the model proposed in this paper can solve the problem of summarization extraction for multi-document very well.
Keywords :
text analysis; automatic summarization; cross structure theory; information fusion; multidocument relationship model; text units; Computational modeling; Automatic Summarization; Information Fusion; Multi-Document Relationship Model; Node;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Natural Computing Proceedings (CINC), 2010 Second International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7705-0
Type :
conf
DOI :
10.1109/CINC.2010.5643796
Filename :
5643796
Link To Document :
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