Searching Service Repositories by Combining Semantic and Ontological Matching
ICWS '05 Proceedings of the IEEE International Conference on Web Services
Similarity search for web services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Autonomic internet-scale workflows
Proceedings of the 3rd International Workshop on Monitoring, Adaptation and Beyond
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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. 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 searching process when composing services. Experimental results indicate that planning with semantic matching produces better results than planning or semantic matching alone. The solution is suitable for semi-automated composition tools or directory browsers.