In data integration, schema matching plays an important role. Present schema matching tools combine various match algorithms, each employing a particular technique to improve matching accuracy. However there is still no fully automatic tool is available and also there is lack of accuracy. As a step in this direction, we have proposed a new and efficient Semantic-Relationship schema matching (SR-Match) approach which considers the semantic relationships as one of the parameters for matching. Here in SR-Match, the initial mappings performed by the basic schema mapping techniques, acts as input to the relationship matcher. Relationship matcher compares the remaining unmapped elements based on their semantic relationship with their parents. It is observed that, if both semantics and relationships are taken into account, the degree of accuracy in matching results is improved. © Springer-Verlag 2011.