Abstract
In this paper, we present an approach to efficiently discover domain-specific services that are described by plain text over the Internet. Plain-text-described service advertisements account for the vast majority of service advertisements over the Internet, but current research rarely focuses on this area. To address this issue, we design a domain-ontology-based approach for automatic plain-text-described service discovery. This approach incorporates a plain-text-described service ontology for standard service description, a plaintext- described service discovery framework for domain-relevant service discovery and ontology learning, and a machine-learning-based model for ontologybased service functionality annotation. The experimental results show that this approach is able to efficiently discover more relevant plain-text-described services than other approaches.
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Dong, H., Hussain, F.K., Bouguettaya, A. (2014). Discovering Plain-Text-Described Services Based on Ontology Learning. In: Loo, C.K., Yap, K.S., Wong, K.W., Beng Jin, A.T., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8836. Springer, Cham. https://doi.org/10.1007/978-3-319-12643-2_81
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DOI: https://doi.org/10.1007/978-3-319-12643-2_81
Publisher Name: Springer, Cham
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