Automatic text summarization using feature based fuzzy extraction

Automatic text summarization is to compress the original text into a shorter version and help the user to quickly understand large volumes of information. This paper focuses on the automatic text summarization by sentence extraction with important features based on fuzzy logic. In our experiment, we...

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Bibliographic Details
Main Authors: Suanmali, Ladda (Author), Salim, Naomie (Author), Binwahlan, Mohammed Salem (Author)
Format: Article
Language:English
Published: Penerbit UTM Press, 2008-12.
Subjects:
Online Access:Get fulltext
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100 1 0 |a Suanmali, Ladda  |e author 
700 1 0 |a Salim, Naomie  |e author 
700 1 0 |a Binwahlan, Mohammed Salem  |e author 
245 0 0 |a Automatic text summarization using feature based fuzzy extraction 
260 |b Penerbit UTM Press,   |c 2008-12. 
856 |z Get fulltext  |u http://eprints.utm.my/id/eprint/9426/1/NaomieSalim2008_AutomaticTextSummarizationUsingFeature-Based.pdf 
520 |a Automatic text summarization is to compress the original text into a shorter version and help the user to quickly understand large volumes of information. This paper focuses on the automatic text summarization by sentence extraction with important features based on fuzzy logic. In our experiment, we used 6 test documents in DUC2002 data set. Each document is prepared by preprocessing process: sentence segmentation, tokenization, remuving Stop Word and stemming Word. Then, we use 8 important features and calculate their score for each sentence. We propose a method using fuzzy logic for sentence extraction and compare our result with the baseline summarizer and Microsoft Word 2007 summarizers. The results show that the highest average precision, recall, and F-mean for the summaries are conducted from fuzzy method. 
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650 0 4 |a QA76 Computer software