Between the data objects there must be cluster relationship which was assumed by clustering methods which they are applied on. Explicitly or implicitly will be defined based upon common things from a pair of objects. In this paper, we explored a novel based upon similarity measure which is multiviewpoint and also couple of clustering methods which are related. There is difference and also it is a major drawback in traditional dissimilarity/similarity measure to ours. The previous method only utilizes a single viewpoint, and then it is treated as origin, while our proposed system deals with a lot various viewpoints. Same cluster objects will not be assumed for measuring. Assessment of similarity will be gained by utilizing multiple viewpoints. Our system is supported with the help of conducting theoretical analysis and empirical study. For document clustering based on this new measure two criterion functions are explored. We measures the similarities and dissimilarities of them with a lot various clustering algorithms that utilizes another well known similarity measures on different document collections to check our proposal advantages.