K-Means Algorithm for Clustering Afaan Oromo Text Documents using Python Tools

With the advancement of technology and proliferation of computers in the country, the amount of Afaan Oromo language news documents produced increasingly which becomes a difficult task for news agencies to organize such huge collection of documents items manually. To solve this problem, researches is conducted using unsupervised machine learning python tools for Afaan Oromo news document clustering with low cost and best quality of clustering solution. In this research work focusing on k-means clustering analysis which produced better results as compared to the other cluster analysis both in terms of time requirement and the quality of the clusters produced.