Data mining and/or knowledge discovery is a very important part of today's e-business. The World Wide Web has become in reality, the largest online information available practically to anyone with access to Internet. An e-business framework is proposed in the paper, as well as the knowledge discovery technique to personalize e-business, increase cross selling, and improve the customer relationship management. Due to the enormous size of the Web and low precision of user queries, results returned from present Web search engines can reach hundreds or even thousands data. Therefore, finding the right information can be difficult if not impossible. One approach that tries to solve this problem is by using clustering techniques for grouping similar data together in order to facilitate presentation of results in more compact form and enable browsing of the results set. In this paper, a data clustering techniques is presented with emphasis on application to Web search results. An algorithm for clustering Web data based on Rough Set is presented and its practical implementation is discussed. © 2007 IEEE.