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Multi document summarization based on cross-document relation using voting technique

News articles which are available through online search often provide readers with large collection of texts. Especially in the case of news story, different news sources reporting on the same event usually returns multiple articles in response to a reader's search. In this work, we first ident...

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Main Authors: Kumar, Yogan Jaya, Salim, Naomie, Abuobieda, Albaraa, Tawfik, Ameer
Format: Conference or Workshop Item
Published: 2013
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/51184/
http://dx.doi.org/10.1109/ICCEEE.2013.6634009
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spelling my.utm.511842017-06-27T04:36:50Z http://eprints.utm.my/id/eprint/51184/ Multi document summarization based on cross-document relation using voting technique Kumar, Yogan Jaya Salim, Naomie Abuobieda, Albaraa Tawfik, Ameer QA75 Electronic computers. Computer science News articles which are available through online search often provide readers with large collection of texts. Especially in the case of news story, different news sources reporting on the same event usually returns multiple articles in response to a reader's search. In this work, we first identify cross-document relations from un-annotated texts using Genetic-CBR approach. Following that, we develop a new sentence scoring model based on voting technique over the identified cross-document relations. Our experiments show that incorporating the proposed methods in the summarization process yields substantial improvement over the mainstream methods. The performances of all methods were evaluated using ROUGE - a standard evaluation metric used in text summarization. 2013 Conference or Workshop Item PeerReviewed Kumar, Yogan Jaya and Salim, Naomie and Abuobieda, Albaraa and Tawfik, Ameer (2013) Multi document summarization based on cross-document relation using voting technique. In: 2013 International Conference on Computer, Electrical and Electronics Engineering: 'Research Makes a Difference', ICCEEE 2013, 2013, Sudan. http://dx.doi.org/10.1109/ICCEEE.2013.6634009
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Kumar, Yogan Jaya
Salim, Naomie
Abuobieda, Albaraa
Tawfik, Ameer
Multi document summarization based on cross-document relation using voting technique
description News articles which are available through online search often provide readers with large collection of texts. Especially in the case of news story, different news sources reporting on the same event usually returns multiple articles in response to a reader's search. In this work, we first identify cross-document relations from un-annotated texts using Genetic-CBR approach. Following that, we develop a new sentence scoring model based on voting technique over the identified cross-document relations. Our experiments show that incorporating the proposed methods in the summarization process yields substantial improvement over the mainstream methods. The performances of all methods were evaluated using ROUGE - a standard evaluation metric used in text summarization.
format Conference or Workshop Item
author Kumar, Yogan Jaya
Salim, Naomie
Abuobieda, Albaraa
Tawfik, Ameer
author_facet Kumar, Yogan Jaya
Salim, Naomie
Abuobieda, Albaraa
Tawfik, Ameer
author_sort Kumar, Yogan Jaya
title Multi document summarization based on cross-document relation using voting technique
title_short Multi document summarization based on cross-document relation using voting technique
title_full Multi document summarization based on cross-document relation using voting technique
title_fullStr Multi document summarization based on cross-document relation using voting technique
title_full_unstemmed Multi document summarization based on cross-document relation using voting technique
title_sort multi document summarization based on cross-document relation using voting technique
publishDate 2013
url http://eprints.utm.my/id/eprint/51184/
http://dx.doi.org/10.1109/ICCEEE.2013.6634009
_version_ 1643652965353914368
score 13.211869

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