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Text Summarization using Centrality Concept

by Ghaleb Algaphari, Fadl M. Ba-alwi, Aimen Moharram
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 79 - Number 1
Year of Publication: 2013
Authors: Ghaleb Algaphari, Fadl M. Ba-alwi, Aimen Moharram
10.5120/13703-1450

Ghaleb Algaphari, Fadl M. Ba-alwi, Aimen Moharram . Text Summarization using Centrality Concept. International Journal of Computer Applications. 79, 1 ( October 2013), 5-12. DOI=10.5120/13703-1450

@article{ 10.5120/13703-1450,
author = { Ghaleb Algaphari, Fadl M. Ba-alwi, Aimen Moharram },
title = { Text Summarization using Centrality Concept },
journal = { International Journal of Computer Applications },
issue_date = { October 2013 },
volume = { 79 },
number = { 1 },
month = { October },
year = { 2013 },
issn = { 0975-8887 },
pages = { 5-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume79/number1/13703-1450/ },
doi = { 10.5120/13703-1450 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:53.184523+05:30
%A Ghaleb Algaphari
%A Fadl M. Ba-alwi
%A Aimen Moharram
%T Text Summarization using Centrality Concept
%J International Journal of Computer Applications
%@ 0975-8887
%V 79
%N 1
%P 5-12
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The amount of textual information available on the web is estimated by terra bytes. Therefore constructing a software program to summarize web pages or electronic documents would be a useful technique. Such technique would speed up of reading, information accessing and decision making process. This paper investigates a graph based centrality algorithm on Arabic text summarization problem (ATS). The graph based algorithm depends on extracting the most important sentences in a documents or a set of documents (cluster). The algorithm starts computing the similarity between two sentences and evaluating the centrality of each sentence in a cluster based on centrality graph. Then the algorithm extracts the most important sentences in the cluster to include them in a summary. The algorithm is implemented and evaluated by human participants and by an automatic metrics. Arabic NEWSWIRE-a corpus is used as a data set in the algorithm evaluation. The result was very promising.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Text Summarization Text Mining and Centrality Concept

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