World Wide Web is a very large distributed digital information space. The ability to search and retrieve information from the Web efficiently and effectively is an enabling technology for realizing its full potential. Current search tools retrieve too many documents, of which only a small fraction are relevant to the user query. Furthermore, the most relevant documents do not necessarily appear at the top of the query output order. Clustering Techniques are now being used to give a meaningful search result on web. Text document clustering has been traditionally investigated as a means of improving the performance of search engines. We present a thorough comparison of the algorithms based on the various facets of their features and functionality. Furthermore, we highlight the main characteristics of a number of existing Web clustering engines and also discuss how to evaluate their retrieval performance.