Ontological framework for trust and reputation for DBE
Today's e-Businesses rely heavily on trust and reputation systems. These systems are key indicators for businesses performance. Businesses that interact with each other for their business needs form a Digital Business Ecosystem (DBE). Members ofDBE need to know the trust and reputation value of...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Conference Paper |
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Institute of Electrical and Electronics Engineers (IEEE)
2008
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/46334 |
| _version_ | 1848757528553324544 |
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| author | Hammadi, Adil Hussain, Farookh Khadeer Chang, Elizabeth Dillon, Tharam S. Ali, S. |
| author2 | E. Chang |
| author_facet | E. Chang Hammadi, Adil Hussain, Farookh Khadeer Chang, Elizabeth Dillon, Tharam S. Ali, S. |
| author_sort | Hammadi, Adil |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Today's e-Businesses rely heavily on trust and reputation systems. These systems are key indicators for businesses performance. Businesses that interact with each other for their business needs form a Digital Business Ecosystem (DBE). Members ofDBE need to know the trust and reputation value of each other before the start of business interactions. The feedback meclwnism is needed so that members of DBE form a unanimous opinion about any specific member of the community and based their business interactions on this opinion. We present an ontological framework that will combine the opinions from aU different trust and reputation databases for a specific member of a domain and gives the knowledge representation on the bases ofcombined opinion. We call this ontological framework feedback ontology. |
| first_indexed | 2025-11-14T09:29:32Z |
| format | Conference Paper |
| id | curtin-20.500.11937-46334 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:29:32Z |
| publishDate | 2008 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-463342022-12-07T06:50:50Z Ontological framework for trust and reputation for DBE Hammadi, Adil Hussain, Farookh Khadeer Chang, Elizabeth Dillon, Tharam S. Ali, S. E. Chang F. Hussain Trust reputation digital business ecosystems ontology Today's e-Businesses rely heavily on trust and reputation systems. These systems are key indicators for businesses performance. Businesses that interact with each other for their business needs form a Digital Business Ecosystem (DBE). Members ofDBE need to know the trust and reputation value of each other before the start of business interactions. The feedback meclwnism is needed so that members of DBE form a unanimous opinion about any specific member of the community and based their business interactions on this opinion. We present an ontological framework that will combine the opinions from aU different trust and reputation databases for a specific member of a domain and gives the knowledge representation on the bases ofcombined opinion. We call this ontological framework feedback ontology. 2008 Conference Paper http://hdl.handle.net/20.500.11937/46334 10.1109/DEST.2008.4635204 Institute of Electrical and Electronics Engineers (IEEE) fulltext |
| spellingShingle | Trust reputation digital business ecosystems ontology Hammadi, Adil Hussain, Farookh Khadeer Chang, Elizabeth Dillon, Tharam S. Ali, S. Ontological framework for trust and reputation for DBE |
| title | Ontological framework for trust and reputation for DBE |
| title_full | Ontological framework for trust and reputation for DBE |
| title_fullStr | Ontological framework for trust and reputation for DBE |
| title_full_unstemmed | Ontological framework for trust and reputation for DBE |
| title_short | Ontological framework for trust and reputation for DBE |
| title_sort | ontological framework for trust and reputation for dbe |
| topic | Trust reputation digital business ecosystems ontology |
| url | http://hdl.handle.net/20.500.11937/46334 |