SEMAPLAN: Combining Planning with Semantic Matching to Achieve Web Service Composition

Composing existing Web services to deliver new functionality is a difficult problem as it involves resolving semantic, syntactic and structural differences among the interfaces of a large number of services. Unlike most planning problems, it can not be assumed that Web services are described using terms from a single domain theory. While service descriptions may be controlled to some extent in restricted settings (e.g., intraenterprise integration), in Web-scale open integration, lack of common, formalized service descriptions prevent the direct application of standard planning methods. In this paper, we present a novel algorithm to compose Web services in the presence of semantic ambiguity by combining semantic matching and AI planning algorithms. Specifically, we use cues from domain-independent and domain-specific ontologies to compute an overall semantic similarity score between ambiguous terms. This semantic similarity score is used by AI planning algorithms to guide the searchin...

• Type: Conference
• Year: 2006
• Where: AAAI
• Authors: Rama Akkiraju, Biplav Srivastava, Anca-Andreea Ivan, Richard Goodwin, Tanveer Fathima Syeda-Mahmood
• Keywords: AAAI 2006, AI Planning Algorithms, Intelligent Agents, Semantic Matching, Semantic Similarity Score