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Reseach Article

Multi-Document and Multi-Lingual Summarization using Neural Networks

Published on April 2012 by M. Karthi Keyan, K. G. Srinivasagan
International Conference in Recent trends in Computational Methods, Communication and Controls
Foundation of Computer Science USA
ICON3C - Number 5
April 2012
Authors: M. Karthi Keyan, K. G. Srinivasagan
9ff8e666-5bfa-469e-bc36-4f0e150a538b

M. Karthi Keyan, K. G. Srinivasagan . Multi-Document and Multi-Lingual Summarization using Neural Networks. International Conference in Recent trends in Computational Methods, Communication and Controls. ICON3C, 5 (April 2012), 11-14.

@article{
author = { M. Karthi Keyan, K. G. Srinivasagan },
title = { Multi-Document and Multi-Lingual Summarization using Neural Networks },
journal = { International Conference in Recent trends in Computational Methods, Communication and Controls },
issue_date = { April 2012 },
volume = { ICON3C },
number = { 5 },
month = { April },
year = { 2012 },
issn = 0975-8887,
pages = { 11-14 },
numpages = 4,
url = { /proceedings/icon3c/number5/6034-1035/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference in Recent trends in Computational Methods, Communication and Controls
%A M. Karthi Keyan
%A K. G. Srinivasagan
%T Multi-Document and Multi-Lingual Summarization using Neural Networks
%J International Conference in Recent trends in Computational Methods, Communication and Controls
%@ 0975-8887
%V ICON3C
%N 5
%P 11-14
%D 2012
%I International Journal of Computer Applications
Abstract

This system proposes Multi-lingual (Tamil and English) Multi-document summarization by neural networks. The system involves three steps. In first step, the sentences of the documents are converted into vector form. In the second step weight values are assigned to vector form based on sentence features. Depend on sentence weight value, single document summarization is done. The output of single document summarization is used as an input for multi-document Summarization. Final step is a sentence selection, in which output summary is selected based on the similarity and dissimilarity measures. Sentence similarity and dissimilarity measures are used to compare the sentences. From that, resultant summary is produced. The proposed system can be able to summarize both Tamil and English online news papers.

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Index Terms

Computer Science
Information Sciences

Keywords

Neural Networks Features Summarization