Review of Document Clustering Methods and Similarity Measurement Methods

Abstract

The process of document clustering is nothing but the data mining method used for grouping of same items together. The clustering approach is aiming to identify the required structures from the input data as well as arranging them into the subgroup. There are many clustering algorithms presented by various authors already such as k-means clustering, Agglomerative Clustering, EM methods, direct clustering methods etc. Each clustering method is having its own advantages and disadvantages. The similarity measure used to measure the similarity between two clusters of input dataset derived from different or similar algorithms. In this paper we are first presenting the review over the document clustering and its different methods, and then later we taking the review of similarity measure method. The techniques of similarity measurements discussed in this paper are used for single viewpoint only. Finally, the limitations of this method are introduced.
DOI: 10.17762/ijritcc2321-8169.1505144