A hybrid service metadata clustering methodology in the digital ecosystems environment
Digital Ecosystems (DE) is an open, loosely coupled, domain clustered, demand-driven, self-organizing and agent-based environment, in which each species is proactive and responsive for its own benefit and profit. Species in DE can play dual roles, which are service requester (client) that needs serv...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
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IEEE Computer Society
2009
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| Subjects: | |
| Online Access: | http://doi.ieeecomputersociety.org/10.1109/WAINA.2009.205 http://hdl.handle.net/20.500.11937/36519 |
| _version_ | 1848754793055518720 |
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| author | Dong, Hai Hussain, Farookh Khadeer Chang, Elizabeth |
| author2 | Tomoya Enokido |
| author_facet | Tomoya Enokido Dong, Hai Hussain, Farookh Khadeer Chang, Elizabeth |
| author_sort | Dong, Hai |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Digital Ecosystems (DE) is an open, loosely coupled, domain clustered, demand-driven, self-organizing and agent-based environment, in which each species is proactive and responsive for its own benefit and profit. Species in DE can play dual roles, which are service requester (client) that needs services and service provider (server) that provides services. A service provider enters DE by publishing a service in the service factory, which will be clustered by domain-specific ontologies provided by DE. Two issues could exist here. The first is that the pre-existing service metadata cannot be easily clustered because of the lack of technological support. To solve this issue, an automatic service metadata clustering method is desired. However, this could educe the second issue the outcome of the method could not agree with service providers perception. To solve the two issues, in this paper, we present an ontology-based metadata clustering methodology, with a complement of a service provider-oriented metadata clustering approach. The information regarding the prototype implementation and the evaluation of this methodology is revealed in the final section. |
| first_indexed | 2025-11-14T08:46:03Z |
| format | Conference Paper |
| id | curtin-20.500.11937-36519 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:46:03Z |
| publishDate | 2009 |
| publisher | IEEE Computer Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-365192019-02-19T05:35:40Z A hybrid service metadata clustering methodology in the digital ecosystems environment Dong, Hai Hussain, Farookh Khadeer Chang, Elizabeth Tomoya Enokido extended case-based reasoning algorithm Digital Ecosystems metadata clustering Digital Ecosystems (DE) is an open, loosely coupled, domain clustered, demand-driven, self-organizing and agent-based environment, in which each species is proactive and responsive for its own benefit and profit. Species in DE can play dual roles, which are service requester (client) that needs services and service provider (server) that provides services. A service provider enters DE by publishing a service in the service factory, which will be clustered by domain-specific ontologies provided by DE. Two issues could exist here. The first is that the pre-existing service metadata cannot be easily clustered because of the lack of technological support. To solve this issue, an automatic service metadata clustering method is desired. However, this could educe the second issue the outcome of the method could not agree with service providers perception. To solve the two issues, in this paper, we present an ontology-based metadata clustering methodology, with a complement of a service provider-oriented metadata clustering approach. The information regarding the prototype implementation and the evaluation of this methodology is revealed in the final section. 2009 Conference Paper http://hdl.handle.net/20.500.11937/36519 http://doi.ieeecomputersociety.org/10.1109/WAINA.2009.205 IEEE Computer Society fulltext |
| spellingShingle | extended case-based reasoning algorithm Digital Ecosystems metadata clustering Dong, Hai Hussain, Farookh Khadeer Chang, Elizabeth A hybrid service metadata clustering methodology in the digital ecosystems environment |
| title | A hybrid service metadata clustering methodology in the digital ecosystems environment |
| title_full | A hybrid service metadata clustering methodology in the digital ecosystems environment |
| title_fullStr | A hybrid service metadata clustering methodology in the digital ecosystems environment |
| title_full_unstemmed | A hybrid service metadata clustering methodology in the digital ecosystems environment |
| title_short | A hybrid service metadata clustering methodology in the digital ecosystems environment |
| title_sort | hybrid service metadata clustering methodology in the digital ecosystems environment |
| topic | extended case-based reasoning algorithm Digital Ecosystems metadata clustering |
| url | http://doi.ieeecomputersociety.org/10.1109/WAINA.2009.205 http://hdl.handle.net/20.500.11937/36519 |