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.
| Author of HS Reutlingen | Zimmermann, Alfred |
|---|---|
| DOI: | https://doi.org/10.1007/978-3-319-19857-6_48 |
| ISBN: | 978-331-91985-7-6 |
| Erschienen in: | Intelligent Decision Technologies : Proceedings of the 7th KES International Conference on Intelligent Decision Technologies (KES-IDT 2015) |
| Publisher: | Springer |
| Place of publication: | Cham |
| Editor: | Rui Neves-Silva |
| Document Type: | Conference proceeding |
| Language: | English |
| Publication year: | 2015 |
| Tag: | BPM; context data; decision-making; process interviews; text mining |
| Page Number: | 12 |
| First Page: | 563 |
| Last Page: | 574 |
| PPN: | Im Katalog der Hochschule Reutlingen ansehen |
| DDC classes: | 006 Spezielle Computerverfahren |
| Open access?: | Nein |
| Licence (German): |  In Copyright - Urheberrechtlich geschützt |
