Track: Semantic Web
Paper Title:
Learning Ontologies to Improve the Quality of Automatic Web Service Matching
Authors:
Abstract:
This paper presents a novel technique that significantly improves
the quality of semantic Web service matching by (1) automatically
generating ontologies based on Web service descriptions and (2)
using these ontologies to guide the mapping between Web services.
The experimental results indicate that with our unsupervised
approach we can eliminate up to 70% of incorrect matches that are
made by dictionary-based approaches.
