Extractive text summarization technique using fuzzy C-means clustering algorithm

bracu.type.groupResearch Publications
datacite.rightsMetadata Only
dc.contributor.authorGani, Shahul
dc.contributor.authorUddin, Jia
dc.contributor.authorMobin, Md. Iftekharul
dc.contributor.departmentDepartment of Computer Science and Engineering,
dc.date.accessioned2026-08-27T11:14:23Z
dc.date.available2026-08-27T11:14:23Z
dc.date.issued2019-07-01
dc.description.abstractText summarization process has become one of the significant research areas for years owing to cope up with the astounding increase of virtual textual materials. Text summarization is the process to keep the relevant important information of the original text in a shorter version with the main ideas of the original text. There are two main classifications of text summarization process Extractive and Abstractive text summarization, Extractive smnmarization processes by using most important fragments of existing words, phrases or sentences from the original document, A sentence based mode) using Fuzzy C-Means clustering has been proposed in this research. Six best key features including a new feature 'Sentence Highlighter Feature' have been introduced for the sentence scoring. Performance of the proposed FCM mode) is evaluated by ROUGE, which has been gauged with the precision, recall and f-measure. The result shows that this FCM model extractive techniques with a less outline repetition and profundity of data.
dc.description.versionPublished
dc.format.extent4 Pages
dc.identifier.citationS. Gani, J. Uddin and M. I. Mobin, "Extractive Text Summarization Technique Using Fuzzy C-Means Clustering Algorithm," 2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2), Rajshahi, Bangladesh, 2019, pp. 1-6, doi: 10.1109/IC4ME247184.2019.9036642.
dc.identifier.doi10.1109/IC4ME247184.2019.9036642
dc.identifier.issn9781728130606
dc.identifier.other2-s2.0-85082988373
dc.identifier.urihttps://hdl.handle.net/10361/29575
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.hasversion10.1109/IC4ME247184.2019.9036642
dc.relation.ispartof5th International Conference on Computer Communication Chemical Materials and Electronic Engineering Ic4me2 2019
dc.relation.ispartofseries5th International Conference on Computer Communication Chemical Materials and Electronic Engineering Ic4me2 2019
dc.relation.urihttps://ieeexplore.ieee.org/document/9036642
dc.subjectClustering algorithms
dc.subjectMathematical model
dc.subjectFeature extraction
dc.subjectSilicon
dc.subjectPartitioning algorithms
dc.subjectChemicals
dc.subjectData mining
dc.subjectSentence extraction
dc.subjectClustering
dc.subjectSummarization
dc.subject.lcshAutomatic abstracting.
dc.subject.lcshNatural language processing (Computer science).
dc.titleExtractive text summarization technique using fuzzy C-means clustering algorithm
dc.typeConference Proceeding
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.identifier.scopus-author-id57216271427
person.identifier.scopus-author-id54994936900
person.identifier.scopus-author-id55545997800

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