Date Added: Nov 2010
Information retrieval mechanisms from the web are a great need of the hour as the amount of the content is growing dynamically every day. There are many algorithms which have been proposed in literature mainly relying on the output of the search engines. These algorithms are either content based or snippet based and perform a clustered outcome re-ranking of the content for the user. This paper proposes a hybrid approach to content clustering that combines the best of the web information retrieval methods and also uses the personal preference information of the users modeling a wide range of contexts.