Conducting data analysis on a large set of documents is not an easy task.The common stages are document filtering, document selection, and document clustering.Clustering is a technique used in Hair oil data mining to find groups of data that do not have a natural grouping.There are many clustering algorithm have been introduced, and two of them are K-means and K-medians.Both methods classify documents based on the proximity of words Flour weighting between documents.
This study aims to compare the quality of the clusters produced by K-means and K-medians.The results show that K-medians obtain a better cluster quality when compared to K-means.However, it takes more time to cluster.