Abstract: A Web Optimization maintains and catalogs the content of Web pages in order to make them easier to find. The importance of WPO is only rising, as well as it grows, the need for tools that can assist developers in making the right also decisions grows. Hence that is the goal of this thesis: to build a tool that can be used for the continuous profiling of a web site's performance. Usually Search Engines search through Web pages for specified keywords. In response they return a list containing those documents containing the specified keywords. This list is sorted by a relevance criterion which tries to put at the very first positions the documents that best match the inquiry of user. In meticulous, since the size of the Web is quickly rising, the central issues observe elevated presentation algorithms for information management. Furthermore, nowadays Web Optimizations receive more searches per day over a collection of several billion web pages indexed. These particular, can easily explain why in such environments the efficiency, as the effectiveness, of Search and Index algorithms have issues became. Intended for this manner in this paper we are going toward proposing novel techniques aimed at enhancing the performance of a Web Optimization from different angles.
Keywords: Web Mining, Web Optimization, k-means Algorithm.