The purely manual specification of semantic correspondences between schemas is almost infeasible for very large schemas or when many different schemas have to be matched. Hence, solving such large-scale match tasks asks for automatic or semi-automatic schema matching approaches. Large-scale matching needs especially be supported for XML schemas and different kinds of ontologies due to their increasing use and size, e.g. in e-business, web and life science applications. Unfortunately, correctly

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... nd efficiently matching large schemas and ontologies is very challenging and most previous match systems have only addressed small match tasks. We provide an overview about recently proposed approaches to achieve high match quality or/and high efficiency for large-scale matching. In addition to describing some recent matchers utilizing instance and usage data, we cover approaches on early pruning of the search space, divide and conquer strategies, parallel matching, tuning matcher combinations, the reuse of previous match results and holistic schema matching. We also provide a brief comparison of selected match tools.