The web is huge, diverse, dynamic, widely distributed global information service center. With the rapid growth of the web, users get easily lost in the rich hyperlink structure. User rely on the web for information, but the currently available search engines often gives a long list of results, much of which are not always relevant to the user’s requirement. Providing relevant information to the users to cater to their needs is the primary goal. Therefore, finding the content of the web and retrieving the users’ interests and needs from their behavior have become increasingly important. The search engine uses these ranking methods to sort the results to be displayed to the user. In that way user can find the most significant and useful result first. Information Retrieval is the activity of obtaining information resources relevant to an information need from a collection of information resources. Therefore in this paper we are proposing an Approach to combine web content, web structure & web usage mining for Enhancing Web Search Engine Results Delivery.For Web Content mining the textual content of web pages is captured through extraction of frequent words using a term-based weighted technique will be combined with hyperlinks using Weighted Page Rank algorithm of Web structure mining which takes into account the importance of both the in-links and the out-links of the pages & Web server log files to discover useful information of user. Finally, the Search result is optimized by re-ranking the result pages. This proposed system proves to be efficient as the pages desired by the user will be on the top priority in the result list and also optimize the query performance in terms of query results. The proposed work will focus on the problem of improving the performance of information retrieval in web search engine results.