K-means hac and fcm which clustering approach for arabic text?

TitreK-means hac and fcm which clustering approach for arabic text?
Publication TypeConference Paper
Year of Publication2020
AuthorsAjallouda, L, Fagroud, FZ, Zellou, A, Benlahmar, EH
Conference NameACM International Conference Proceeding Series
Mots-clésArabic texts, Classification (of information), Classification approach, Clustering approach, Intelligent systems, Internet users, K-means clustering, Rapid growth, Real case, Textual data, Web resources
Abstract

Today we are witnessing rapid growth in Web resources that allow Internet users to express and share their ideas opinions and judgments on a variety of issues. Several classification approaches have been proposed to classify textual data. But all these approaches require us to label the clusters we want to obtain. Which in reality is not available because we do not know in advance the information that can be proposed through these opinions. To overcome this constraint clustering approaches such as K-mean HAC or FCM can be exploited. In this paper we present and compare these approaches. And to show the importance of exploiting clustering algorithms to classify and analyze textual data in Arabic. By applying them to a real case that has created a great debate in Morocco which is the case of teachers contracting with academies. © 2020 ACM.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85096415898&doi=10.1145%2f3419604.3419779&partnerID=40&md5=8aca383d8f485d15b3da191f03c5bf62
DOI10.1145/3419604.3419779
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