Suanmali, Ladda and Wahlan, Mohammed Salem and Salim, Naomie (2009) Sentence features fusion for text summarization using fuzzy logic. In: Proceedings - 2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009. Institute of Electrical and Electronics Engineers, New York, 142 -146. ISBN 978-076953745-0
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Official URL: http://dx.doi.org/10.1109/HIS.2009.36
The scoring mechanism of the text features is the unique way for determining the key ideas in the text to be presented as text summary. The efficiency of the technique used for scoring the text sentences could produce good summary. The feature scores are imprecise and uncertain, this marks the differentiation between the important features and unimportant is difficult task. In this paper, we introduce fuzzy logic to deal with this problem. Our approach used important features based on fuzzy logic to extract the sentences. In our experiment, we used 30 test documents in DUC2002 data set. Each document is prepared by preprocessing process: sentence segmentation, tokenization, removing stop word, and word stemming. Then, we use 9 important features and calculate their score for each sentence. We propose a method using fuzzy logic for sentence extraction and compare our results with the baseline summarizer and Microsoft Word 2007 summarizers. The results show that the highest average precision, recall, and F-measure for the summaries were obtained from fuzzy method.
|Item Type:||Book Section|
|Additional Information:||2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009; Shenyang; 12 August 2009 through 14 August 2009|
|Uncontrolled Keywords:||fuzzy logic, sentence features, text summarization|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System|
|Deposited By:||Liza Porijo|
|Deposited On:||18 Jul 2011 07:55|
|Last Modified:||18 Jul 2011 07:55|
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