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Process Discovery and Guidance Applications of Manually Generated Logs

Title data

Schönig, Stefan ; Günther, Christoph ; Jablonski, Stefan:
Process Discovery and Guidance Applications of Manually Generated Logs.
In: International Academy, Research, and Industry Association - IARIA (ed.): The Seventh International Conference on Internet Monitoring and Protection. - Wilmingston, DE : IARIA , 2012 . - pp. 61-67 . - 8 S.
ISBN 978-1-61208-201-1

Official URL: Volltext

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Abstract in another language

In this paper, we investigate the problem of the availability of complete process execution event logs in order to offer automatic process model generation (process discovery) possibility by process mining techniques. Therefore, we present our AI4 | Process Observation Project that generates manual logs and guides process participants through process execution. Like this, our project offers the possibility for the automatic generation of process models within organizations, without the availability of any information system. Process participants are encouraged to work with our AI4 | Process Observation Tool by various process execution support functions, like an auto-suggestion of process data and dynamic recommendations of following processes.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Process Mining; Process Monitoring; Activity Tracking; Guidance through Process Execution
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV > Chair Applied Computer Science IV - Univ.-Prof. Dr.-Ing. Stefan Jablonski
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 23 Oct 2017 12:22
Last Modified: 23 Oct 2017 12:22
URI: https://eref.uni-bayreuth.de/id/eprint/34896