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The composition of distributed resources is a pervasive challenge facing almost all modern application fields, especially for large-scale scientific applications. In most of these applications, several resources need to be integrated in order to fulfill the requirements of a complex scientific task. However, even though current Web Services have emerged as a paradigm for managing complex distributed resources, the lack of machine readability in representation prevents Web Services from supporting the efficient composition of resources. This paper presents SECPlanner, a new Web Services composition approach which combines the AI Planning Graph technique with semantics enabled matchmaking algorithm to find the optimal composition candidates. The composition result will afterwards be represented as a scientific workflow for future reuse.