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dc.contributor.authorRaza, Muhammad
dc.contributor.authorHussain, Farookh Khadeer
dc.contributor.authorHussain, Omar
dc.contributor.authorChang, Elizabeth
dc.contributor.editorKoen Vanhoof
dc.contributor.editorDa Ruan
dc.contributor.editorTianrui Li
dc.contributor.editorGeert Wets
dc.date.accessioned2017-01-30T10:52:38Z
dc.date.available2017-01-30T10:52:38Z
dc.date.created2010-03-30T20:02:20Z
dc.date.issued2009
dc.identifier.citationRaza, Muhammad and Hussain, Farookh Khadeer and Hussain, Omar and Chang, Elizabeth. 2009. Optimizing trust prediction in digital business ecosystem, in Koen Vanhoof, Da Ruan, Tianrui Li and Geert Wets (ed), 2009 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2009), Nov 27 2009, pp. 1-9. Hasselt, Belgium: World Scientific Proceedings Series.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/6373
dc.description.abstract

The process of predicting the future trust value of an entity, based on its past value is a challenging issue. The prediction process is even more imperative in the scenario where in the interaction would take place at a future point in time. Being able to determine the confidence value of the predicted trust value is of prime importance to enable optimized trust prediction. In this paper we propose a set of metrics for determining the confidence level in the predicted trust value.

dc.publisherWorld Scientific Proceedings Series
dc.titleOptimizing trust prediction in digital business ecosystem
dc.typeConference Paper
dcterms.source.startPage1
dcterms.source.endPage9
dcterms.source.titleProceedings of the 2009 international conference on intelligent systems and knowledge engineering (ISKE 2009)
dcterms.source.seriesProceedings of the 2009 international conference on intelligent systems and knowledge engineering (ISKE 2009)
dcterms.source.isbn9789814295055
dcterms.source.conference2009 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2009)
dcterms.source.conference-start-dateNov 27 2009
dcterms.source.conferencelocationHasselt, Belgium
dcterms.source.placeBelgium
curtin.departmentDigital Ecosystems and Business Intelligence Institute (DEBII)
curtin.accessStatusOpen access
curtin.facultyCurtin Business School
curtin.facultyThe Digital Ecosystems and Business Intelligence Institute (DEBII)


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