Search engines give so many results that a user cannot handle them all in a short period of time. Many approaches have been proposed to alleviate this problem. For example, some approaches try to add personalized features and some try to group the results into different categories. The latter one is called a clustering engine, which is the emphasis of this paper. It first reviews several existing approaches such as STC, SHOC, LINGO and SnakeT. It then gives a new approach called HICSEC (Hierarchical Clustering Search Engine with Correlation) to improve the accuracy of clustering by the Correlation calculated with the Singular Value Decomposition.