A fuzzy approach based for document datasets clustering
Joint Authors
Hadi, Raghad Muhammad
Mawlud, Abir Tariq
Hashim, Sukaynah Hasan
Source
Journal of College of Education for Pure Sciences
Issue
Vol. 9, Issue 1 (31 Mar. 2019), pp.1-13, 13 p.
Publisher
University of Thi-Qar College of Education for Pure Sciences
Publication Date
2019-03-31
Country of Publication
Iraq
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
In large Computers; the huge volume of files actually generate disorder to analyze it.
So, it desires to design a clustering techniques which reduce the costs of analysts.
Document clustering is an essential process in text mining, which retrieve the information with an acceptable accuracy, which can be achieved by fuzzy clustering.
Reuters 21578 dataset is used for experimental purpose; the proposed system was tested by using Reuters 21578 datasets according to the time required to cluster data.
The proposed system improves data clustering algorithms by construct required fuzzy clusters.
The proposed system showed a good result compared with clustering techniques in comparing with other clustering techniques in time efficiency.
American Psychological Association (APA)
Hadi, Raghad Muhammad& Hashim, Sukaynah Hasan& Mawlud, Abir Tariq. 2019. A fuzzy approach based for document datasets clustering. Journal of College of Education for Pure Sciences،Vol. 9, no. 1, pp.1-13.
https://search.emarefa.net/detail/BIM-891561
Modern Language Association (MLA)
Hadi, Raghad Muhammad…[et al.]. A fuzzy approach based for document datasets clustering. Journal of College of Education for Pure Sciences Vol. 9, no. 1 (Mar. 2019), pp.1-13.
https://search.emarefa.net/detail/BIM-891561
American Medical Association (AMA)
Hadi, Raghad Muhammad& Hashim, Sukaynah Hasan& Mawlud, Abir Tariq. A fuzzy approach based for document datasets clustering. Journal of College of Education for Pure Sciences. 2019. Vol. 9, no. 1, pp.1-13.
https://search.emarefa.net/detail/BIM-891561
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 12-13
Record ID
BIM-891561