IJIRCSTJournal International Journal of Innovative Research in Computer Science and Technology I S Volume 2 Issue 5 Information Technology English September - October 2014 N N Y 2019 11 21 Computer Sciences Usage of Cosine Similarity and term Frequency count for Textual document Clustering English Y 9 12 B. Sindhuja English Y Mrs. VeenaTrivedi English N This paper presents textual document clustering using two approaches namely cosine similarity and frequency and inverse document frequency. With the combination of these approaches a similarity measure values are generated between keywords in the documents and between the documents. Using this approach, the best related document can be identified on the basis of clustering method called correlation preserving index in which related documents are stored in an index format. English Document Clustering, Cosine similarity, Tf-idf, Correlation preserving index. https://ijircst.org/abstract.php?article_id=96