Abstract: Systems, methods and computer program products for the ranking of a target data set based on learned rules are disclosed. One embodiment is a method that includes generating a learned rule set from a training data record set, creating at least one prototype for each rule in the learned rule set to generate a prototype set, and ranking the target data record set using learned rule set and the prototype set. The generating of a learned rule set includes dividing the training data record set to a positive class and a negative class, and deriving the learned rule set for the positive class. Learning of rules includes deriving the most general projected rules with respect to remaining training data and then refining those rules, eventually selecting the best rules using an F-measure.

Abstract: Systems, methods and computer program products for the ranking of a target data set based on learned rules are disclosed. One embodiment is a method that includes generating a learned rule set from a training data record set, creating at least one prototype for each rule in the learned rule set to generate a prototype set, and ranking the target data record set using learned rule set and the prototype set. The generating of a learned rule set includes dividing the training data record set to a positive class and a negative class, and deriving the learned rule set for the positive class. Learning of rules includes deriving the most general projected rules with respect to remaining training data and then refining those rules, eventually selecting the best rules using an F-measure.