Trusting Information Sources One Citizen at a Time
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Toward autonomic web services trust and selection
Proceedings of the 2nd international conference on Service oriented computing
Agent-based trust model involving multiple qualities
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
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In the context of the Semantic Web, it may be beneficial for a user to receive a forecast regarding the reliability of an information source. We offer an algorithm for building more effective social networks of trust by using CLRM (classic linear regression models). For managing uncertainty, we introduce some random variables which neither the consumer nor the provider can control its value. Such random variables that can be successively accumulated from each stage of multi-stage forecasts are reduced through the use of analytical tools that combine statistical methods with advances in time series analysis. Time series analysis can relate 'current' values of a critical variable to its past values and to the values of current. Moreover, to model real world scenario, VAR-GARCH (Vector Auto Regression Generalized Autoregressive Conditional Heteroskedasticity) model is used to represent forecasting results which are generally influenced by interactions between decision makers.