This study addresses the information overload problem that one faces while browsing the results of a web search query. The increasing indexing capabilities of the commercial web search engines makes it common for a broadly formulated search query to result in thousands of web documents. This causes a nontrivial overload problem. Our study proposes the use of clustering and information visualization as a remedy to this problem. The proposed prototype system groups the search results according to their contents. The information seeker is presented a visual overview of these clusters to identify the general characteristics of the document collection. Based on such an understanding of the information space, the user of the system can focus on document groups of more interest in order to reach the information sought for. We will incorporate two different zooming methods for this purpose: the traditional full zoom (strict-filtering), and a fisheye zoom which provides details in context. We will empirically test the success of the visualization based presentation system in comparison to its text based counterpart in an experimental setting. The success of the fisheye zoom approach in comparison to the full zoom approach will also be tested by means of the same experiment.