A semantic web service classification system
Semantic Web Services allows web services to be searchable through discovery, composition and invocation and monitoring. Existing systems, such as MODiCo [1], allows automatic semantic web service discovery and composition but at high computational costs. By considering only web services in...
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2010
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sg-ntu-dr.10356-362782023-03-03T20:34:13Z A semantic web service classification system Tan, Jui Kian. Goh Eck Soong, Angela School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Semantic Web Services allows web services to be searchable through discovery, composition and invocation and monitoring. Existing systems, such as MODiCo [1], allows automatic semantic web service discovery and composition but at high computational costs. By considering only web services in the domain of interest, the effectiveness and efficiency of web service discovery and composition are expected to be improved significantly. Hence, a Semantic Web Service Classification System is proposed. The classification system is designed with high speed performance and classification accuracies in mind. With these two criteria in mind, pure textual descriptions approach has been selected as the main approach in dealing with the task of semantic web service classification. Supervised machine learning algorithms are used with this approach. Experiments have shown that implementing a semantic web service classification system for existing systems, such as MODiCo, is feasible. Our approach is able to achieve good classification accuracies and speed performance using SVM as the machine learning algorithm. Top three classification results can be used to further improve the classification system. Further work such as multi-labeled classification methods and optimization of machine learning algorithms are areas worth researching. Bachelor of Engineering (Computer Engineering) 2010-04-30T02:35:03Z 2010-04-30T02:35:03Z 2010 2010 Final Year Project (FYP) http://hdl.handle.net/10356/36278 en Nanyang Technological University 63 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Tan, Jui Kian. A semantic web service classification system |
description |
Semantic Web Services allows web services to be searchable through discovery,
composition and invocation and monitoring. Existing systems, such as MODiCo [1],
allows automatic semantic web service discovery and composition but at high
computational costs. By considering only web services in the domain of interest, the
effectiveness and efficiency of web service discovery and composition are expected to be
improved significantly. Hence, a Semantic Web Service Classification System is
proposed.
The classification system is designed with high speed performance and classification
accuracies in mind. With these two criteria in mind, pure textual descriptions approach
has been selected as the main approach in dealing with the task of semantic web service
classification. Supervised machine learning algorithms are used with this approach.
Experiments have shown that implementing a semantic web service classification system
for existing systems, such as MODiCo, is feasible. Our approach is able to achieve good
classification accuracies and speed performance using SVM as the machine learning
algorithm. Top three classification results can be used to further improve the
classification system. Further work such as multi-labeled classification methods and
optimization of machine learning algorithms are areas worth researching. |
author2 |
Goh Eck Soong, Angela |
author_facet |
Goh Eck Soong, Angela Tan, Jui Kian. |
format |
Final Year Project |
author |
Tan, Jui Kian. |
author_sort |
Tan, Jui Kian. |
title |
A semantic web service classification system |
title_short |
A semantic web service classification system |
title_full |
A semantic web service classification system |
title_fullStr |
A semantic web service classification system |
title_full_unstemmed |
A semantic web service classification system |
title_sort |
semantic web service classification system |
publishDate |
2010 |
url |
http://hdl.handle.net/10356/36278 |
_version_ |
1759856917300117504 |