Semantic filtering for DDL-based service composition

Abstract

Dynamic description logic (DDL) provides a good logic-level solution among the few emerging service composition solutions through reasoning in AI area. To make DDL reasoning infrastructure practical, there is still unaddressed needs of increasing reasoning efficiency. We proposed a semantic filtering approach aiming to increase reasoning efficiency through decreasing reasoning space. The filtering approach was decomposed into two consecutive steps: context-based semantic retrieval with iRDQL -(an imprecise query model, and processing of retrieval results under the control of workflow before forming final filtering results. Experimental results show that the method is well suitable for the volatile context-aware environment and yields good performance over DDL-based service composition. © 2008 Springer Berlin Heidelberg.