This document summarizes an article on automatic document clustering. It discusses how documents are preprocessed using techniques like tokenization, stop word removal, and stemming before being clustered. Clustering algorithms group similar documents together based on similarity metrics like TF-IDF. Documents can be searched by name, extension, or keywords to retrieve them from the clustered storage in a faster and more organized manner. Future work may include clustering multimedia files and improving algorithm performance.