Solving matching problems in computer science entails generating alignments between structured data. Well known examples are schema matching, process model matching, ontology alignment, and Web service composition. Design of software systems aimed at solving these problems, and refinement of interim results, are aided by solution quality evaluation measures. Historically, measures have been based upon binary set-theory, required an expert generated exact-match and assumed a single expert review following the algorithmic effort. Motivated by new applications for data integration, the dissertation both extends commonly used measures and proposes new measures to support evaluation in a variety of scenarios. We review the measures proposed to date and present an outlook towards future work.