Introducing groups to the MADCOW annotation system solves the privacy-collaboration problem for users, while defining a proper matching between groups and users solved the group join problem for both groups’ owners and users. We use ontological and URL-based measures to execute the match. For ontological-based measures, MADCOW are used and linked with external knowledge repositories: ontologies. The URL-based measure gives a quantification of shared interests by considering the number of URLs annotated by both group members and MADCOW users external to the group. In this work, we describe the system, the problems, and their solutions, with reference to the design choices made.