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Automated knowledge discovery and semantic annotation for network and web services

Author

Listed:
  • Szu-Yin Lin
  • Chia-Chen Chung
  • Wei-Che Hu
  • Chihli Hung
  • Shih-Lun Chen
  • Ting-Lan Lin

Abstract

With the rise of the Internet of things, the smart environmental issue is becoming increasingly important. Sensor web is one of the best solutions to this issue and provides the advantages of sensor networks and web services. Ontology web language for services (OWL-S) is an OWL-based web services ontology, which provides the ability to describe the semantics of web services and their capabilities in a formal and machine-processable manner. Moreover, it aids semantic service matching, selection and composition. However, automatically annotating semantic web services is a highly complicated and tedious task. In this study, we propose a methodology to uncover information in the history data and profiles of web services and then semantically annotate them. With the proposed approach, semantic relationships between web services could be extracted via a combination of association rules and input/output matching. Our results show that this hybrid automated knowledge-discovery approach works better than traditional approaches do. We also provide a scenario to explain how the proposed methodology works.

Suggested Citation

  • Szu-Yin Lin & Chia-Chen Chung & Wei-Che Hu & Chihli Hung & Shih-Lun Chen & Ting-Lan Lin, 2016. "Automated knowledge discovery and semantic annotation for network and web services," International Journal of Distributed Sensor Networks, , vol. 12(7), pages 15501477166, July.
    • Handle: RePEc:sae:intdis:v:12:y:2016:i:7:p:1550147716657925
    DOI: 10.1177/1550147716657925
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