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In this work a model is engineered to depict topic relationships as graphs between detected topics of different time windows. By varying and shifting the time span of consideration the relationships between topics can be mapped with a variable complexity including the topic frequencies. Topic life cycles as well as changes in thematic relationships and their evolution become perceptible. Topics found can be matched in structure as well as their temporal progression to existing events.

Themen-Graphen, Themen-Frequenz, Text Mining, Dokumentenstrom, topic-graph, topic-frequency, text mining, document streams

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How can people with different knowledge and experience use process models in the digital communication and at the same time how can they receive system support through the described processes? This question is solved by a mutual transformation based on natural language which is illustrated with practical examples. Thus, more widespread workflows can be implemented by incorporating system boundaries that were previously hard to overcome.

Geschäftsprozessmodellierung, Kommunikationssysteme, automatische Sprachverarbeitung, Textmodelltransformation, Workflowmanagement, Business Process Modeling, Communication Systems, Natural Language Processing, Text Model Transformation, Workflow Management