Recommendation system based on statistical analysis of ranking from user

Search queries on large databases, often return a large number of results, only a small subset of which is relevant to the user. When the user want to search the result for a particular query he or she find lot of difficulties when query results are large in size. To overcome the searching and navigation difficulty the following contributions are made. Design very good user interface to search the query using front end tools like ASP.NET and it will fetch the result from database like SQL SERVER 2005.For personalized recommendation system Advanced Encryption Standard algorithm is used to get the user feedback in secured format. Query results are organized into a tree format using tree control. Using several real-world ratings the comprehensive empirical evaluation shows diversity gains of proposed techniques. Ranking concept is used to display the concepts in order based on more number of times that concept is accessed. Edge cut algorithm is used to display the query result mostly related to the user expected results in tree format. Graph is generated based on spatial attributes. Ranking and categorization, which can also be combined, have been proposed to alleviate this information overload problem.