In this paper, we propose an approach to presenting web search results that supports personalization, taking into consideration users' perspectives. We developed a post-retrieval algorithm which uses document classification techniques to organize search results into a meaningful hierarchy of topics, based on the perspective of the user performing the search, represented as a taxonomic ontology. A ... [Show full abstract] demonstration system called WEBCLUSTERS was implemented to interface with a number of existing search engines to retrieve search results for keyword queries and present them in user defined topic hierarchies. The classification of retrieved documents to a concept in an ontology is based on the multinomial variant of the naïve Bayes classifier. Experiments were performed to measure the accuracy of the system in organizing documents based on user-defined ontologies. Accuracy was measured by estimating the degree of correlation between two different ontologies which described the same information domain. Experiments show that where the retrieved documents are heterogeneous in nature, the WEBCLUSTERS system is capable of classifying search results into the user specified hierarchy with a reasonable level of accuracy.