Abstract. The aim of this thesis is to develop a faceted classification and clustering system for results of web searches. The system has been built on top of Freemind, a mind-mapping editor tool. With our system, the user is able to create a map of thoughts and search for information concerning a topic of this map in the World Wide Web. Our system focuses on retrieving papers. For a resulting list of papers, facets and clusters are created. The facets concern fields such as ‘date’, ‘authors’, ‘published in’, ‘publication type’, ‘general terms’ and ‘categories and subject descriptors’. The first four facets are created based on information retrieved from the DBLP database, whereas the last two are based on information retrieved directly after parsing and processing the content of papers (where available). In fact, each facet imposes a filtering criterion on the results. The user can add, remove or change such criteria, by changing the values of each facet. The clustering task is performed using text content from the papers. Papers are organized in groups. Papers in each group are considered to be relevant to the same topic.