Computational requirement of schema matching algorithms

The integration of different data structures e.g. relational databases of information systems is a current issue in the area of information sciences. Numerous solutions aroused recently aiming to achieve a high accuracy in similarity measurement and integration of schema entities coming from different schemas. Researches usually properly evaluate the capabilities of these approaches from the point of view of accuracy. However the computational complexity of the proposed algorithms is hardly ever examined in the most of these works. We claim that efficiency of a solution can only be judged by taking into account both the accuracy and the computational requirements of participating algorithms. Since there are many known measurement methods and metrics for the evaluation of accuracy, the focus is set for the analysis of their computational complexity in this paper. After the problem formulation the main ideas behind our method are presented. Various approximation techniques and methods of applied algorithm theory are used to evaluate the different approaches. Three specific approaches were also selected to present the work of our method in details on them. Experiments run on several test inputs are also included. Key-Words: Computational complexity, Schema matching, Approximation techniques in computational requirement estimation