Ontology Learning for Cost-Effective Large-Scale Semantic Annotation of Web Service Interfaces
2010 (English)In: Knowledge Engineering and Management by the Masses, EKAW 2010, Springer Berlin/Heidelberg, 2010, 401-410 p.Conference paper (Refereed)
In this paper we introduce a novel unsupervised ontology learning approach, which can be used to automatically derive a reference ontology from a corpus of web services for annotating semantically the Web services in the absence of a core ontology. Our approach relies on shallow parsing technique from natural language processing in order to identify grammatical patterns of web service message element/part names and exploit them in construction of the ontology. The generated ontology is further enriched by introducing relationships between similar concepts. The experimental results on a set of global Web services indicate that the proposed ontology learning approach generates an ontology, which can be used to automatically annotate around 52% of element part and field names in a large corpus of heterogeneous Web services.
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2010. 401-410 p.
, Lecture Notes in Computer Science, ISSN 0302-9743 ; 6317
NLP, Ontology Learning, Web Services Annotation
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-74919DOI: 10.1007/978-3-642-16438-5_30ISI: 000312832300030ScopusID: 2-s2.0-78650236201ISBN: 978-3-642-16437-8OAI: oai:DiVA.org:kth-74919DiVA: diva2:490189
17th International Conference on Knowledge Engineering and Management by the Masses, EKAW 2010; Lisbon; 11 October 2010 through 15 October 2010
QC 201203012012-02-042012-02-042013-12-19Bibliographically approved