Title
A Frequency-Based Algorithm for Workflow Outlier Mining
Abstract
The concept of workflow is critical in the ERP (Enterprise Resources Planning) system. Any workflow that is irrationally and irregularly designed will not only lead to an ineffective operation of enterprise but also limit the implementation of an effective business strategy. The research proposes an algorithm which makes use of the workflow's executed frequency, the concept of distance-based outlier detection, empirical rules and Method of Exhaustion to mine three types of workflow outliers, including less-occurring workflow outliers of each process (abnormal workflow of each process), less-occurring workflow outliers of all processes (abnormal workflow of all processes) and never-occurring workflow outliers (redundant workflow). In addition, this research adopts real data to evaluate workflow mining feasibility. In terms of the management, it will assist managers and consultants in (1) controlling exceptions in the process of enterprise auditing, and (2) simplifying the business process management by the integration of relevant processes.
Year
DOI
Venue
2010
10.1007/978-3-642-17569-5_21
Lecture Notes in Computer Science
Keywords
Field
DocType
ERP,BPM,Workflow mining,Data mining,Outlier detection
Business process management,Data mining,Computer science,Algorithm,Business process modeling,Business process discovery,Workflow engine,Workflow,Event-driven process chain,Enterprise data management,Process mining
Conference
Volume
ISSN
Citations 
6485
0302-9743
2
PageRank 
References 
Authors
0.38
11
4
Name
Order
Citations
PageRank
Yu-Cheng Chuang142.44
Ping-Yu Hsu227641.77
MinTzu Wang362.15
Sin-Cheng Chen420.38