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Evaluating the potential of a prospective candidate is a common task inmultiple decision-making processes in different industries. We refer to aprospect as something or someone that could potentially produce positiveresults in a given context, e.g., an area where an oil company could find oil,a compound that, when synthesized, results in a material with requiredproperties, and so on. In many contexts, assessing the Probability of Success(PoS) of prospects heavily depends on experts' knowledge, often leading tobiased and inconsistent assessments. We have developed the framework named KARA(Knowledge-augmented Risk Assessment) to address these issues. It combinesmultiple AI techniques that consider SMEs (Subject Matter Experts) feedback ontop of a structured domain knowledge-base to support risk assessment processesof prospect candidates in knowledge-intensive contexts.

Knowledge-augmented Risk Assessment (KaRA): a hybrid-intelligence  framework for supporting knowledge-intensive risk assessment of prospect  candidates