Abstract: A computer implemented method for document clustering comprises receiving one or more documents via one or more input means, arranging the one or more documents into a term-document matrix using term frequency-inverse document frequency, removing and stemming of one or more common clutter/stop words from the one or more documents, extracting one or more features from the one or more documents using non-negative matrix factorization (NMF) and k means, determining one or more vectors based on the one or more features, implementing k-means clustering thereby iterating the one or more documents and the one or more features and clustering the one or more documents based on similarity between the extracted one or more features and the each of the one or more documents.