Sentence features fusion for text summarization using fuzzy logic

dc.contributor.authorLadda Suanmali
dc.contributor.authorMohammed Salem Binwahlan
dc.contributor.authorNaomie Salim
dc.contributor.correspondenceL. Suanmali; Faculty of Science and Technology, Suan Dusit Rajabhat University, Bangkok, 10300, Thailand; email: ladda_sua@dusit.ac.th
dc.date.accessioned2025-03-10T07:38:08Z
dc.date.available2025-03-10T07:38:08Z
dc.date.issued2009
dc.description.abstractThe 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. © 2009 IEEE.
dc.identifier.citationProceedings - 2009 9th International Conference on Hybrid Intelligent Systems, HIS 2009
dc.identifier.doi10.1109/HIS.2009.36
dc.identifier.isbn978-076953745-0
dc.identifier.scopus2-s2.0-70450184501
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/5057
dc.languageEnglish
dc.rights.holderScopus
dc.subjectFuzzy logic
dc.subjectSentence features
dc.subjectText summarization
dc.titleSentence features fusion for text summarization using fuzzy logic
dc.typeConference paper
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-70450184501&doi=10.1109%2fHIS.2009.36&partnerID=40&md5=85721691808c7614301b3ca0012d351f
oaire.citation.endPage146
oaire.citation.startPage142
oaire.citation.volume1
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