Learning Business Rules for Adaptive Process Models
No Thumbnail Available
Authors
Author (Corporation)
Publication date
2012
Typ of student thesis
Course of study
Collections
Type
04B - Conference paper
Editors
Editor (Corporation)
Supervisor
Parent work
BUSTECH 2012 - Second International Conference on Business Intelligence and Technology
Special issue
DOI of the original publication
Link
Series
Series number
Volume
Issue / Number
Pages / Duration
Patent number
Publisher / Publishing institution
Place of publication / Event location
Nice
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
This work presents a new approach to handling knowledge-intensive business processes in an adaptive, flexible and accurate way. We propose to support processes by executing a process skeleton, consisting of the most important recurring activities of the process, through a workflow engine. This skeleton should be kept simple. The corresponding workflow is complemented by two features: firstly, a task management tool through which workflow tasks are delivered and that give human executors flexibility and freedom to adapt tasks by adding subtasks and resources as required by the context. And secondly, a component that learns business rules from the log files of this task management and that will predict subtasks and resources on the basis of knowledge from previous executions. We present supervised and unsupervised approaches for rule learning and evaluate both on a real business process with 61 instances. Results are promising, showing that meaningful rules can be learned even from this comparatively small data set.
Keywords
Data Mining, process mining
Subject (DDC)
330 - Wirtschaft
Event
Second International Conference on Business Intelligence and Technology (BUSTECH 2012)
Exhibition start date
Exhibition end date
Conference start date
Conference end date
Date of the last check
ISBN
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
License
Citation
HINKELMANN, Knut, Hans Friedrich WITSCHEL und Tuan Q. NGUYEN, 2012. Learning Business Rules for Adaptive Process Models. In: BUSTECH 2012 - Second International Conference on Business Intelligence and Technology. Nice. 2012. Verfügbar unter: http://hdl.handle.net/11654/10774