The constant growth of the Web in recent years hasmade more difficult the discovery of new sources of informationon a given topic. This is a prominent problem for Experts inIntelligence Analysis (EIA) who are faced with the search of pageson specific and sensitive topics. Because of their lack of popularityor because they are poorly indexed due to their sensitive content,these pages are hard to find with traditional search engines. Inthis article, we describe a new Web source discovery system calledDOWSER (Discovery Of Web Sources Evaluating Relevance).The goal of this system is to provide users with new sourcesof information related to their needs without considering thepopularity of a page unlike classic Information Retrieval tools.The expected result is a balance between relevance and originality,in the sense that the wanted pages are not necessary popular.DOWSER is based on a user profile to focus its exploration of theWeb in order to collect and index only related Web documents.As requests can be insufficient to express sensitive and specificneeds, the user’s information needs are specified using user’sinterests represented by DBPedia resources [1] and keywords,both extracted from Web pages provided by the user. A series ofexperiments provides an empirical evaluation of DOWSER.