We propose a semi-automatic ontology matching system using a hybrid active learning and online learning approach. Following the former paradigm, those mappings whose validation is estimated to lead to greater quality gain are selected for user validation, a process that occurs in each iteration, following the online learning paradigm. Experimental results demonstrate the effectiveness of our approach.