To Determine Document Clustering By using Centroid Ratio for Pair wise Random Swap Clustering Algorithm?

Clustering algorithm and cluster validity are two highly correlated parts in cluster analysis. In this paper, a novel idea for cluster validity and a clustering algorithm based on the validity index are introduced. A Centroid Ratio is firstly introduced to compare two clustering results. This centroid ratio is then used in prototype-based clustering by introducing a Pair wise Random Swap clustering algorithm to avoid the local optimum problem of k-means. Before clustering, the number of clusters is an essential parameter for the clustering algorithm, while after clustering; the validity of the clustering is performed. The similarity value for comparing two clusterings from the centroid ratio can be used as a stopping criterion in the algorithm.