Nowadays, developers of web application mashups face a sheer overwhelming variety and pluralism of web
services. Therefore, choosing appropriate web services to achieve specific goals requires a certain amount of
knowledge as well as expertise. In order to support users in choosing appropriate web services it is not only
important to match their search criteria to a dataset of possible choices but also to rank the results according
to their relevance, thus minimizing the time it takes for taking such a choice. Therefore, we investigated six
ranking approaches in an empirical manner and compared them to each other. Moreover, we have had a look
on how one can combine those ranking algorithms linearly in order to maximize the quality of their outputs.