Using Machine Learning Techniques for Evaluating the Similarity of Enterprise Architecture Models

Enterprises Architectures (EA) are facilitated to coordinate enterprise’s business visions and strategies successfully and effectively. The practitioners of EA (architects) communicate the architecture to other stakeholders via architecture models. We investigate the scenario where accepted architecture models are stored in a repository. We identified the problem of unnecessary repository expansion by adding model components with similar properties or behavior as already existing repository components. The proposed solution aims to find those similar components and to notify the architect about their existence.