Semantic Matching to Achieve Web Service Discovery and Composition

Authors:
Rama Akkiraju;Anca Ivan;Richard Goodwin;Biplav Srivastava;Tanveer Syeda-Mahmood
Affiliations:
IBM T. J. Watson Research Center, NY;IBM T. J. Watson Research Center, NY;IBM T. J. Watson Research Center, NY;IBM India Research Laboratory, Block 1, IIT Campus, Hauz Khaus, New Delhi, India;IBM Almaden Research Center, 650 Harry Road, San Jose, CA
Venue:
CEC-EEE '06 Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services
Year:
2006

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Abstract

In this paper, we present a novel algorithm to discover and 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 searching process when composing services. In addition, we integrate semantic and ontological matching with an indexing method, which we call attribute hashing, to enable fast lookup of semantically related concepts.