Abstract: A system modeling meta-model language model for a system is extracted from a natural language specification of the system. Syntactic structure is extracted from the specification of a system. The syntactic structure represents a set of at least one syntactic subject. A first mapping is created between a predetermined set of the at least one syntactic subject and respective meta-model elements for a system modeling meta-model language. At least one of the meta-model elements is constructed in accordance with the mapping for each identified syntactic subject. The created meta-model structural elements are created for conversion into a model of the system.

Abstract: An event processing system in which a computer receives an input event comprising one or more factors. The computer evaluates the factors of the input event based on an event processing rule containing a pattern detection operator and a conditional probability operator. The conditional probability operator can operate to calculate a conditional probability for a set of training data that a specified pattern will appear in the factors of an input event given a specified output event, and can further operate to assign a conditional rule value a binary value based on how the conditional probability compares to a target probability.

Abstract: A system modeling meta-model language model for a system is extracted from a natural language specification of the system. Syntactic structure is extracted from the specification of a system. The syntactic structure represents a set of at least one syntactic subject. A first mapping is created between a predetermined set of the at least one syntactic subject and respective meta-model elements for a system modeling meta-model language. At least one of the meta-model elements is constructed in accordance with the mapping for each identified syntactic subject. The created meta-model structural elements are created for conversion into a model of the system.