Abstract: At least one embodiment of the present invention is directed to a method and/or an apparatus for automatically providing a common modelling pattern as a function of a plurality of stored process models. The common modelling patterns are identified according to three substeps, namely semantic annotation, extraction of pattern based description and composite process pattern mining. The detected common modelling patterns serve as best practice candidates as regards process engineering. At least one embodiment of the present invention finds application in a variety of domains being related to process management, such as process design, process mining and semantic process planning.

Abstract: A method and an apparatus for automatic extraction of process model comprising model elements named by natural language expressions and annotated with semantic linkages to a reference process ontology are disclosed. The process model is split into partial process models by which an annotated partial process model is created. Process goals are decoupled from each annotated partial and hierarchical process goal tree is generated for each annotated partial process model.

Abstract: The invention relates to an apparatus for clustering process models each consisting of model elements comprising a text phrase which describes in a natural language a process activity according to a process modeling language grammar and a natural language grammar, wherein said apparatus comprises a process object ontology memory for storing a process object ontology, a distance calculation unit for calculating a distance matrix employing said processing modeling language grammar and said natural language grammar, wherein said distance matrix consists of distances each indicating a dissimilarity of a pair of said process models, and a clustering unit which partitions said process models into a set of clusters based on said calculated distance matrix.

Abstract: At least one embodiment of the present invention is directed to a method and/or an apparatus for automatically providing a common modelling pattern as a function of a plurality of stored process models. The common modelling patterns are identified according to three substeps, namely semantic annotation, extraction of pattern based description and composite process pattern mining. The detected common modelling patterns serve as best practice candidates as regards process engineering. At least one embodiment of the present invention finds application in a variety of domains being related to process management, such as process design, process mining and semantic process planning.

Abstract: The invention relates to a method and a system for automatic extraction of process goals from a semantically annotated structured process model comprising model elements named by natural language expressions and annotated with semantic linkages to a reference process ontology comprising the steps of: splitting said process model having at least one end event into partial process models provided for each end event of said process model; annotating the model elements of each partial process model with a process goal extracted from said model element; and decoupling of the process goals from each annotated partial process model to generate a hierarchical process goal tree for each annotated partial process model.

Abstract: The invention relates to an apparatus for clustering process models each consisting of model elements comprising a text phrase which describes in a natural language a process activity according to a process modeling language grammar and a natural language grammar, wherein said apparatus comprises a process object ontology memory for storing a process object ontology, a distance calculation unit for calculating a distance matrix employing said processing modeling language grammar and said natural language grammar, wherein said distance matrix consists of distances each indicating a dissimilarity of a pair of said process models, and a clustering unit which partitions said process models into a set of clusters based on said calculated distance matrix.