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Leveraging textual information for improving decision making in the business process lifecycle

  • Business process implementations fail, because requirements are elicited incompletely. At the same time, a huge amount of unstructured data is not used for decision-making during the business process lifecycle. Data from questionnaires and interviews is collected but not exploited because the effort doing so is too high. Therefore, this paper shows how to leverage textual information for improving decision making in the business process lifecycle. To do so, text mining is used for analyzing questionnaires and interviews.

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Name:Zimmermann, Alfred
Erschienen in:Intelligent Decision Technologies : Proceedings of the 7th KES International Conference on Intelligent Decision Technologies (KES-IDT 2015)
Place of publication:Cham
Editor:Rui Neves-Silva
Document Type:Conference Proceeding
Year of Publication:2015
Tag:BPM; context data; decision-making; process interviews; text mining
First Page:563
Last Page:574
Catalogue entry:Im Katalog der Hochschule Reutlingen ansehen
Dewey Decimal Classification:006 Spezielle Computerverfahren
Open Access:Nein
Licence (German):License Logo  Lizenzbedingungen Springer