About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Conference paper
FUSE-BEE: Fusion of subjective opinions through behavior estimation
Abstract
Information is critical in almost all decision making processes. Therefore, it is important to get the right information at the right time from the right sources. However, information sources may behave differently while providing information - i.e., they may provide unreliable, erroneous, noisy, or misleading information deliberately or unintentionally. Motivated by this observation, in this paper, we propose a statistical information fusion approach based on behavior estimation. Our approach transforms the conveyed information into more useful form by tempering them with the estimated behaviors of sources. Through extensive simulations, we have shown that our approach has a lower computational complexity, and achieves significantly low behavior estimation and fusion errors.