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Service computing is emerging as a promising computing paradigm to offer the convenience for users to resolve complex business process problems on an integrated, large-scale, distributed and heterogeneous Internet environments. To successfully execute a business process, the workflow creation by depending on service discovery techniques should be made in the first place. Particularly, semantics have been proposed as a key to automatically solving service discovery problem for facilitating users create a workflow. However, most of semantic service discovery and composition methods still remain at a low efficiency stage because they generally involve time consuming ontology reasoning and manual processing. To address this problem, we present an efficient service discovery and composition method by building quick service query list (QSQL) to support automated processes for creating a workflow. QSQL is an efficient service index list which can be dynamically built by service publication algorithm. In QSQL, semantic relationships between the published services and all related ontology concepts can be processed in advance and simultaneously recorded in QSQL data model so that the large number of ontology reasoning can be avoided at service discovery stage. Further, our proposed algorithms can efficiently select and combine service models from QSQL to match a user query.