Text Clustering using K-MEAN

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 (https://www.kaggle.com/lucasturtle/national-anthems-of- the-world ).