Analysis of Indian News Headlines Using Text Clustering

This paper focuses on categorising the Indian news headlines in a more apt way using clustering algorithms. The paper uses document frequency to convert the text into a format that can be passed to the clustering algorithm. All work is done in the Python language. The work uses all pre-processing methods of natural language processing but faces limitations due to the use of manual methods of naming. The aim was to increase the accuracy of clustering and labelling news headlines by using text frequency. It is expected to have a follow up using natural language processing algorithms for automated labelling.