The B!SON project, conducted jointly by TIB and SLUB Dresden, implements a recommender system for quality-assured open access journals. The recommender system will filter a list sorted by relevance from the large number of available open access journals. For this purpose, in addition to common bibliometric methods of similarity determination, machine learning methods will be used to determine the semantic similarity between user inputs (especially abstract and cited literature of the article to be published). The partners cooperate with OpenCitations and the Directory of Open Access Journals and strive for a close exchange with institutions that advise authors. While open access publishing requirements are steadily increasing and there are a growing number of open access journals, authors often lack knowledge of relevant, quality-assured open access journals that would be suitable for publishing their own research. A freely accessible tool that can be linked to local support structures will help to make the transition to open access successful.