Using Historical Accuracy of User Decision Making to Improve Accuracy of Predictive Modeling Based Automatic Classification

A plurality of user made decisions concerning unknown data objects are received from a plurality of users. Each specific user made decision concerns a specific unknown data object made by a specific user, wherein the specific decision could not be made automatically with a sufficient level of confidence without user input. Accuracy of the received user made decisions is automatically determined, as empirical data determinative of the accuracy of the decisions becomes available over time. User weights are automatically dynamically calculated, based on the determined accuracy of decisions made by associated users. Multiple user made decisions received from multiple users concerning a specific unknown data object are aggregated, taking into account the user weights. A definitive decision concerning the specific unknown data object is automatically made without prompting any user for confirmation, based on the aggregating of the user made decisions concerning the specific unknown data object.