A Bayesian approach for incorporating expert opinions into decision support systems

摘要: Interest in the use of (big) company data and data-mining models to guide decisions exploded recent years. In many domains there are human experts whose knowledge is essential building, interpreting applying these models. However, impact integrating expert opinions into decision-making process has not been sufficiently investigated. This research gap deserves attention because triangulation information sources critical for success analytical projects. paper contributes literature by (a) detailing natural advantages Bayesian framework fusing multiple one decision support system (DSS), (b) confirming necessity adjusted methods this data-explosion era, (c) opening path future applications DSSs other organizational contexts. concrete, we propose a that formally fuses subjective with more objective information. We empirically test proposed fusion approach context customer-satisfaction prediction study show how it improves performance model ignoring introduces fuse sources.Fusing big ensures higher-quality decisions.The demonstrates advantage machinery fusion.