Automated knowledge discovery and semantic annotation for network and web services
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 on...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2016-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147716657925 |
| _version_ | 1797708743941554176 |
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| author | Szu-Yin Lin Chia-Chen Chung Wei-Che Hu Chihli Hung Shih-Lun Chen Ting-Lan Lin |
| author_facet | Szu-Yin Lin Chia-Chen Chung Wei-Che Hu Chihli Hung Shih-Lun Chen Ting-Lan Lin |
| author_sort | Szu-Yin Lin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T06:25:54Z |
| format | Article |
| id | doaj.art-6e11f8d7ad8c40c2a7bb7eb108a9c9e1 |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T06:25:54Z |
| publishDate | 2016-07-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-6e11f8d7ad8c40c2a7bb7eb108a9c9e12023-09-03T01:53:39ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772016-07-011210.1177/1550147716657925Automated knowledge discovery and semantic annotation for network and web servicesSzu-Yin Lin0Chia-Chen Chung1Wei-Che Hu2Chihli Hung3Shih-Lun Chen4Ting-Lan Lin5Department of Information Management, Chung Yuan Christian University, Taoyuan City, TaiwanInstitute of Information Management, National Chiao Tung University, Hsin-Chu City, TaiwanDepartment of Information Management, Chung Yuan Christian University, Taoyuan City, TaiwanDepartment of Information Management, Chung Yuan Christian University, Taoyuan City, TaiwanDepartment of Electronic Engineering, Chung Yuan Christian University, Taoyuan City, TaiwanDepartment of Electronic Engineering, Chung Yuan Christian University, Taoyuan City, TaiwanWith 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.https://doi.org/10.1177/1550147716657925 |
| spellingShingle | Szu-Yin Lin Chia-Chen Chung Wei-Che Hu Chihli Hung Shih-Lun Chen Ting-Lan Lin Automated knowledge discovery and semantic annotation for network and web services International Journal of Distributed Sensor Networks |
| title | Automated knowledge discovery and semantic annotation for network and web services |
| title_full | Automated knowledge discovery and semantic annotation for network and web services |
| title_fullStr | Automated knowledge discovery and semantic annotation for network and web services |
| title_full_unstemmed | Automated knowledge discovery and semantic annotation for network and web services |
| title_short | Automated knowledge discovery and semantic annotation for network and web services |
| title_sort | automated knowledge discovery and semantic annotation for network and web services |
| url | https://doi.org/10.1177/1550147716657925 |
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