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Leveraging Incrementally Enriched Domain Knowledge to Enhance Service Categorization

Jia Zhang, Jian Wang, Patrick Hung, Zheng Li, Neng Zhang, Keqing He

Source Title: International Journal of Web Services Research (IJWSR)9(3)

ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781466614758|DOI: 10.4018/jwsr.2012070103

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MLA

Zhang, Jia, et al. "Leveraging Incrementally Enriched Domain Knowledge to Enhance Service Categorization." IJWSR vol.9, no.3 2012: pp.43-66. http://doi.org/10.4018/jwsr.2012070103

APA

Zhang, J., Wang, J., Hung, P., Li, Z., Zhang, N., & He, K. (2012). Leveraging Incrementally Enriched Domain Knowledge to Enhance Service Categorization. International Journal of Web Services Research (IJWSR), 9(3), 43-66. http://doi.org/10.4018/jwsr.2012070103

Chicago

Zhang, Jia, et al. "Leveraging Incrementally Enriched Domain Knowledge to Enhance Service Categorization," International Journal of Web Services Research (IJWSR) 9, no.3: 43-66. http://doi.org/10.4018/jwsr.2012070103

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Abstract

This paper reports the authors’ study over an open service and mashup repository, ProgrammableWeb, which groups stored services into predefined categories. Leveraging such a unique structural feature and hidden domain knowledge of the service repository, they extend the Support Vector Machine (SVM)-based text classification technique to enhance service-oriented categorization. An iterative approach is presented to automatically verify and adjust service categorization, which will incrementally enrich domain ontology and in turn enhance the accuracy of service categorization.

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Leveraging Incrementally Enriched Domain Knowledge to Enhance Service Categorization

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