Diversity based text summarization

Diversity of selected sentences is an important factor in automatic text summarization to control redundancy in the summarized text. In paper, we propose a method called maximal marginal importance (MMI) for text summarization based on the idea of the well-known diversity approach maximal marginal r...

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Main Authors: Binwahlan, Mohammed Salem, Salim, Naomie, Suanmali, Ladda
Format: Article
Language:English
Published: Penerbit UTM Press 2008
Subjects:
Online Access:http://eprints.utm.my/9422/
http://eprints.utm.my/9422/1/NaomieSalimKPFSKSM2008_DiversityBasedTextSummarization.pdf
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author Binwahlan, Mohammed Salem
Salim, Naomie
Suanmali, Ladda
author_facet Binwahlan, Mohammed Salem
Salim, Naomie
Suanmali, Ladda
author_sort Binwahlan, Mohammed Salem
building UTeM Institutional Repository
collection Online Access
description Diversity of selected sentences is an important factor in automatic text summarization to control redundancy in the summarized text. In paper, we propose a method called maximal marginal importance (MMI) for text summarization based on the idea of the well-known diversity approach maximal marginal relevance (MMR) where an emphasis is on the diversity based binary tree is used to exploit the diversity among the document sentences, where the whole document is clustered into a number of clusters, and then each cluster is presented as one binary tree or more. In our method, the sentence is evaluated based on its importance and its relevance. Our experimental results shown that the proposed method outperforms the three benchmark methods used in this study.
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spelling utm-94222017-11-01T04:17:21Z http://eprints.utm.my/9422/ Diversity based text summarization Binwahlan, Mohammed Salem Salim, Naomie Suanmali, Ladda QA75 Electronic computers. Computer science Diversity of selected sentences is an important factor in automatic text summarization to control redundancy in the summarized text. In paper, we propose a method called maximal marginal importance (MMI) for text summarization based on the idea of the well-known diversity approach maximal marginal relevance (MMR) where an emphasis is on the diversity based binary tree is used to exploit the diversity among the document sentences, where the whole document is clustered into a number of clusters, and then each cluster is presented as one binary tree or more. In our method, the sentence is evaluated based on its importance and its relevance. Our experimental results shown that the proposed method outperforms the three benchmark methods used in this study. Penerbit UTM Press 2008-12 Article PeerReviewed application/pdf en http://eprints.utm.my/9422/1/NaomieSalimKPFSKSM2008_DiversityBasedTextSummarization.pdf Binwahlan, Mohammed Salem and Salim, Naomie and Suanmali, Ladda (2008) Diversity based text summarization. Jurnal Teknologi Maklumat, 20 (2). pp. 1-11. ISSN 0128-3790
spellingShingle QA75 Electronic computers. Computer science
Binwahlan, Mohammed Salem
Salim, Naomie
Suanmali, Ladda
Diversity based text summarization
title Diversity based text summarization
title_full Diversity based text summarization
title_fullStr Diversity based text summarization
title_full_unstemmed Diversity based text summarization
title_short Diversity based text summarization
title_sort diversity based text summarization
topic QA75 Electronic computers. Computer science
url http://eprints.utm.my/9422/
http://eprints.utm.my/9422/1/NaomieSalimKPFSKSM2008_DiversityBasedTextSummarization.pdf