Abstract: Methods and computer apparatus are disclosed for deriving first order logic language rules for use in analyzing new data to identify anomalies in the new data. Historical data is formatted to be in a form suitable for application of a machine-learning algorithm thereto. The machine-learning algorithm is applied to the formatted historical data to generate a set of first order logic language rules that cover the formatted historical data. The set of first order logic language rules are analyzed to obtain a subset of said set of first order logic language rules which can be used as first order logic language rules in analyzing new data.

Abstract: A computer-implemented method for automatically generating learning exercises, including determining a target learning item in response to an event, obtaining a knowledge level of a learner in relation to the target learning item based on a model of the learner as produced by an automated learner model, associating a level of difficulty with the obtained knowledge level of the learner, retrieving a learning exercise pattern from an exercise pattern database, automatically generating a learning exercise relating to the retrieved learning exercise pattern based on the model of the learner and the associated level of difficulty; and presenting the learning exercise to the learner via an exercise interface.