The aim of this Master’s thesis is to examine the retrieval performance of two search engines, Yahoo! News and Sesam, specialized on indexing news articles in Swedish. Thirty search questions were used in this study, divided into three different categories: domestic news, amusement and sport. Precision has been calculated both for the 30 search questions as a total and for the three categories as well. Precision was calculated at every DCV-level and then divided with the number of search questions used, in an attempt to reach an average measure. An analysis was also used were precision was calculated over all the DCV-levels for each question in attempt to see how the search engines perform for a given search question and a given search engine. The relevance of the top 10 retrieved documents was judged using a binary scale. The result of the study shows little difference in precision between the two search engines. Yahoo! News performs slightly better than Sesam in most cases. The results show much variation between the search engines regarding how they perform per given search question. Much of the underlying techniques used by the search engines is not know for the public why the methods used in the study, for example the terms chosen as search terms, choice of highest DCV-level et cetera, and how these different choices made may had an impact on the result in the study is discussed rather than underlying technical functions. / Uppsatsnivå: D