Title
Retrieval and clustering for supporting business process adjustment and analysis
Abstract
In this paper, we describe a framework able to support run-time adjustment and a posteriori analysis of business processes, which exploits the retrieval step of the Case-based Reasoning (CBR) methodology. In particular, our framework allows to retrieve traces of process execution similar to the current one. Moreover, it supports an automatic organization of the trace database content through the application of hierarchical clustering techniques. Results can provide help both to end users, in the process execution phase, and to process engineers, in (formal) process conformance evaluation and long term process schema redesign. Retrieval and clustering rely on a distance definition able to take into account temporal information in traces. This metric has outperformed simpler distance definitions in our experiments, which were conducted in a real-world application domain.
Year
DOI
Venue
2014
10.1016/j.is.2012.11.006
Inf. Syst.
Keywords
Field
DocType
business process,long term process schema,distance definition,process execution,process conformance evaluation,business process adjustment,hierarchical clustering technique,retrieval step,real-world application domain,process execution phase,simpler distance definition,hierarchical clustering
Hierarchical clustering,Data mining,Business process,End user,Computer science,A priori and a posteriori,Application domain,Cluster analysis,Business process discovery,Schema (psychology),Database
Journal
Volume
ISSN
Citations 
40,
0306-4379
11
PageRank 
References 
Authors
0.56
43
2
Name
Order
Citations
PageRank
Stefania Montani190181.42
Giorgio Leonardi217920.36