Justified performance measurement of schema matching solutions

Due to the heterogeneity of softwares used by companies, Enterprise Application Integration faces many challenges, one of which is the matching of schemas. In order to be able to launch and maintain communication among these applications, their interfaces should be semantically mapped. Many promising schema matching solutions have been proposed throughout the last decade and we could witness some convincing performance on their side. However, our research effort has proven that their performance may vary on a large scale if they are not set up properly for the given scenario. One potential source of inaccuracy could be the false classification of entity pairs bearing semantic distances close to the threshold value. In order to lessen this distortion effect, we propose a new approach to evaluate the accuracy of schema matching solutions and we also propose refinement to our existing accuracy measure maximization technique. Our new approach would then enable to gain justified accuracy values, while retaining the basics of the classic accuracy evaluation.