WWW2007 Poster Details
Poster Title:
Learning Ontologies to Improve the Quality of Automatic Web Service Matching
Authors:
  • Hui Guo (Stony Brook University)
  • Anca Ivan (IBM T.J. Watson Research Center)
  • Rama Akkiraju (IBM T.J. Watson Research Center)
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.
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