Titlebook: Enterprise, Business-Process and Information Systems Modeling; 17th International C Rainer Schmidt,Wided Guédria,Sérgio Guerreiro Conferenc

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What Have We Unlearned Since the Early Days of the Process Movement? tasks, with mostly an implicit outcome. It is about time we went back to the early principles of BPR and connected people by explicitly showing the collaboration between the actors of the process, the outcome of the process, and only then designing the activities and their sequence.

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Semi-automatic Derivation of RESTful Interactions from Choreography Diagramsthod is based on natural language analysis techniques to derive interactions from the textual information in choreography diagrams. The proposed method is evaluated in terms of effectiveness and considered to be useful by REST developers.

ferment

Automatic Signature Generation for Anomaly Detection in Business Process Instance Dataatic signature generation approach for textual business process instance data while respecting its contextual attributes. Its efficiency is shown by an comprehensive evaluation that applies the approach on thousands of realistic data entries and 240,?000 anomalous data entries.

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Conference proceedings 2016human perspectives; new directions in process modeling; consistency, correctness and compliance; process and data mining; and process variability..The intention of EMMSAD is to solicit papers related to the field of information systems analysis and design including numerous information modeling meth

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漸強(qiáng)

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Considering Social Distance as an Influence Factor in the Process of Process Modelinges us to show significant differences between low and high social distance with respect to the quality, granularity, and structure of the created process models. The results obtained give insights into how enterprises shall compose teams for creating and evolving process models.

Keshan-disease

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Hybrid Diagnosis Applied to Multiple Instances in Business Processesfaults that simultaneously combines business rules and data of multiple process instances. This process is based on Constraint Programming paradigm to efficiently ascertain a minimal diagnosis. Furthermore, a methodology for calculation of the most appropriate degree of likelihood of faults in data