Ontology matching is concerned with finding relations between elements of different ontologies. In large-scale settings, some significant challenges arise, such as how to achieve a reduction in the time it takes to perform matching and how to improve the quality of results. Current techniques involve the use of ontology segmentation to overcome having such a large number of elements to compare. However, current methods usually select the most relevant ontology elements based on the number of relationships, which may dismiss some elements should they have fewer or no relationships. Therefore, we propose an algorithm for ontology segmentation based on application requirements, in such a way that the users can specify the concepts that are the most relevant in their application context to generate the segments which will be used as an input for the matching. In the experiments, we found a general reduction in the execution time and some significant quality improvements, depending on what matcher is applied. In order to assess the proposed algorithm, we considered some well-known evaluation measures, such as precision, recall, and F-Measure.