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Text Clustering using K-MEAN

Journal: International Journal of Advanced Trends in Computer Science and Engineering (IJATCSE) (Vol.10, No. 4)

Publication Date:

Authors : ;

Page : 2892-2897

Keywords : ;

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Document clustering allows the user to add similar documents to a group. For many years, it has been a fascinating research topic, developed various methods and techniques. However, the study focuses mostly on English and high-resource languages. About Pakistan national anthems, this research gives an experimental estimation of clustering techniques. Because of its short length, thematically clustering Anthem is a difficult task. This paper extracted various characteristics, including stop-words, stemming, corpus tokenization, noise removal, and TF-IDF features from the anthem, and the clustering was conducted using the K-Means algorithm. The results show that a clustering strategy paired with a K-mean clustering algorithm with TF-IDF features has already been used. The dataset is available on GitHub ( the-world ).

Last modified: 2021-08-11 21:39:16